Jump to:

• What are Observability Tools?
• Observability vs Monitoring: What are the Differences?
• Top Observability Tools Comparison
• How to Choose the Right Observability Tool

What are Observability Tools?

Back to top

Observability tools measure system outputs to help IT teams understand what’s happening internally at any given time. To accomplish this, these platforms aggregate three types of system-wide telemetry data:

• Metrics, which are performance-related KPI measurements such as memory usage and transactions per second
• Logs, which are unstructured, qualitative records of events taking place within a system
• Traces, which connect the dots between sequential events

However, observability is greater than the sum of its parts. You must be able to view all of the information in one place for it to have any significant meaning. That’s where an observability platform provides value. With an observability platform in place, you can identify what the issue is, where it’s happening, and which systems are impacted. It can also tell you what caused the issue in the first place and what you can do to fix it. 

Continue reading about the future of observability: Observability’s Growth to Evolve into Automation Solutions in 2022

Observability vs Monitoring: What are the Differences? 

Back to top

Observability and monitoring are closely related, but they are distinct concepts. Monitoring tools like application performance monitoring (APM) software have historically been used to record information about events as they happen. For example, they alert DevOps and SRE teams if an application is down or if any problems need to be resolved. However, they fall short of providing a holistic view of an enterprise’s distributed application environment. 

This is where observability solutions come into play. Observability platforms take the information gathered from monitoring tools and help identify patterns that would be otherwise obscured. Observability also makes it easier to pinpoint the root cause of a system-wide problem, whereas monitoring only provides the basis for a trial-and-error strategy. In many ways, monitoring tools are like a patient’s pulse oximeter, and observability platforms are like the patient’s team of doctors that use the blood oxygen information to diagnose broader health issues.

In summary, monitoring answers questions about what’s happening at any given time; observability takes this one step further to identify the why. In the context of this relationship, better monitoring leads to better observability, and unreliable monitoring makes observability impossible.

Learn more about monitoring: Best System Monitoring Software & Tools 2022

Top Observability Tools Comparison

Back to top

New Relic

Back to chart

New Relic is a veteran in the observability market, and it’s stayed on pace with evolving tech trends and enterprise needs. The platform offers straightforward instrumentation and easily customizable dashboards. Plus, you can choose from more than 400 “quickstarts” that provide one-click integrations, dashboards, and alerts with the top software tools you use day-to-day.

Several users have commented that New Relic’s interface has a very clean and modern design that presents information in a visually appealing way. However, a nice GUI isn’t always intuitive or easy to navigate. In fact, some users have mentioned that clicking into different areas of the platform may lead to calls and emails from the sales team if the particular feature requires an upgrade.

Pricing

New Relic offers four pricing plans. All plans include unlimited basic users, 100 GB of data, and one free full platform user.

• Free: $0, with limited data and users
• Standard: 
  • $0.25/GB beyond included 100 GB 
  • $99/full platform user (1 included for free, maximum 5 total)
  • $49/Core User
• Pro: Contact sales for customized pricing
• Enterprise: Contact sales for customized pricing

Honeycomb

Back to chart

Honeycomb was built with an observability-first approach, which means it’s supremely positioned to help Dev, DevOps, and SRE teams operate more efficiently. No matter how complex your system is, Honeycomb provides a single view of all business events. One of the most impactful features is BubbleUp, Honeycomb’s tool that points you toward the correct dimension of an outlier event that’s causing issues.

Some users have noted that the Honeycomb interface can be a bit clunky or overwhelming when you’re starting out, but the platform offers extensive step-by-step tutorials to get up and running. On a similar note, a few users have commented that Honeycomb’s approach to observability lacks some of the traditional monitoring capabilities like live reporting and long-term data retention. Depending on your needs, this may be a drawback or a non-issue.

Pricing

Honeycomb’s pricing is more straightforward than most observability platforms on the market. There are three pricing plans you can choose from:

• Free: $0, with limited support, event volume, and triggers
• Pro: Starting at $100/month
• Enterprise: Contact sales for customized pricing

Splunk

Back to chart

Splunk has been a giant in the APM market for nearly two decades, and it currently offers a smorgasbord of observability apps. There are individual solutions for infrastructure monitoring, APM, logging, front-end user monitoring, synthetic monitoring, and automated incident response. You can choose to add each of these apps à la carte, or you can bundle them for one monthly fee under the Splunk Observability Cloud.

One of the biggest benefits of Splunk is that its instrumentation features natively support OpenTelemetry, an open-source observability framework. This advantage means the whole platform is completely vendor-agnostic and provides a consistent structure for collecting telemetry data across applications. With this simplicity in your backend, you and your teams can spend more time improving app features and performance.

Pricing

There are many different ways you can slice and dice the Splunk Observability Cloud platform, but the top packages come down to full-stack observability or end-to-end observability:

• Standard (full-stack observability): starts at $95/host/month
• Plus (end-to-end observability): starts at $110/host/month

Dynatrace

Back to chart

Similar to Splunk, Dynatrace is an all-in-one platform for full-stack observability, application monitoring and security, digital experience, business analytics, and cloud automation. However, what makes Dynatrace unique is its AI engine, Davis. Davis provides precise, automated insights about your system data instantly and continuously. These insights include dependency detection, anomaly detection, root cause analysis, and business impact analysis.

One drawback of the platform, however, is that Dynatrace’s pricing structure means it can get pretty expensive to implement. Several users have noted how high the total cost of ownership can get, especially if you want a truly all-in-one solution. The AI capabilities are unique, though, so it may be worth the extra cost in the long run.

Pricing

Dynatrace’s pricing is modular-based:

• Full-stack monitoring: Starting at $69/month
• Infrastructure monitoring: Starting at $21/month
• Digital experience monitoring: Starting at $11/month
• Application security: Starting at $12/month
• Open ingestion: Starting at $25/month
• Cloud automation: Starting at $0.12/Cloud Automation Unit

Lightstep

Back to chart

Lightstep is a relatively new player in the observability market, but its features are competitive with many of the market leaders. It uses the same OpenTelemetry framework as Splunk, plus a unique change intelligence tool that correlates events and anomalies then provides context for all alerts. Many users have also praised Lightstep for its ease of use and clean, intuitive design.

Because Lightstep is newer, though, many of the features are still maturing. The search functionality leaves much to be desired at times, and some users have reported slow performance. However, the Lightstep team releases new updates frequently, so they’re constantly evaluating where they have room for improvement. 

Pricing

Lightstep offers three pricing plans:

• Community: Free
• Teams: Starting at $100/month
• Enterprise: Contact sales for volume discounts

How to Choose the Right Observability Tool

The perfect observability tool will offer the features you need, integrate with the tools you use to develop and manage your applications, and stay within your budget. More importantly, though, it will help your DevOps and SRE teams operate more efficiently. In turn, this helps improve customer experience and drive broader business goals.

After reviewing the observability tools on this list, you still might be unsure which solution is the best for your organization. The best way to narrow it down is to read testimonials from customers like you, so you can get a better understanding of how each platform will meet your needs. Then, explore the free editions of your top picks or consider starting a free trial to test drive them for yourself before committing to one.

Read next: AI and Observability Platforms to Alter DevOps Economics

The post Top Observability Tools & Platforms 2022 appeared first on IT Business Edge.

Jump to:

• Blue Prism vs UiPath: Bot Automation
• Blue Prism vs UiPath: Interface
• Blue Prism vs UiPath: Scalability
• Blue Prism vs UiPath: Cost
• The Best RPA Tool for Your Business

Blue Prism vs UiPath: Bot Automation

One of the biggest core differences between Blue Prism and UiPath is the kinds of bots they offer. Blue Prism only offers unattended bots for back-office processes. This has major implications for your business’s overall productivity and operational efficiency, but very little impact on your employees’ individual productivity. 

That’s where UiPath has an advantage — with UiPath, you have the option to run both attended and unattended bots. This means your employees can collaborate with attended bots directly from their desktops while unattended bots operate using logic-based triggers in the background. 

Also read: Finding Value in Robotic Data Automation

Blue Prism vs UiPath: Interface

Blue Prism and UiPath also have distinct approaches to their user experience. UiPath’s interface is extremely user-friendly. Its drag-and-drop functionality means general business users won’t need any programming knowledge to create automations. Plus, UiPath is accessible from a mobile app and desktop browsers, whereas Blue Prism is only available through a desktop application.

Blue Prism has been on the market longer than UiPath, and it shows in the look and feel of the outdated interface. One customer noted, “The software looks like Windows 98 compared to slicker, newer software such as UiPath.” The fact that Blue Prism is intended for behind-the-scenes automation means the user interface isn’t as important, but you’ll still need intermediate coding experience to make use of the platform.

Blue Prism vs UiPath: Scalability

What Blue Prism lacks in user-friendliness and versatility it makes up for in reliability at scale. The platform is capable of supporting as many robots as you create, whereas UiPath reaches capacity at 10,000 robots per server. The higher the workload, the less stable the UiPath platform becomes.

UiPath has been known to crash even with medium-sized RPA projects, whereas Blue Prism will maintain reliable performance as your business’s automation needs grow. Additionally, Blue Prism’s debugging capabilities for large-scale operations are smoother and more dynamic compared to UiPath’s more tedious processes.

Also read: Laying the Groundwork for Modern IT Automation

Blue Prism vs UiPath: Cost

Blue Prism and UiPath are at opposite ends of the spectrum when it comes to cost. On one end, UiPath’s pricing is straightforward and more affordable to get started. There’s also a free community edition that’s perfect for learners or a limited number of users. This affordability is great if you’re just getting started with RPA, but the long-term costs may be less effective as you scale.

On the other hand, Blue Prism’s investment costs are higher than UiPath but more economical in the long run. You’ll be responsible for a more expensive price per bot, but Blue Prism has fewer hardware requirements than UiPath. This means your overall operating costs may be lower with Blue Prism, especially as your RPA needs grow.

The Best RPA Tool for Your Business

Blue Prism and UiPath are two of the best RPA tools on the market. However, it may be difficult to choose between the two even after comparing their bot automation capabilities, interface, scalability, and costs. 

Blue Prism might be the better choice if you need a scalable long-term solution and can manage a higher upfront cost. However, UiPath might be the right tool for you if you need a solution that’s versatile and user-friendly for all skill levels.

If you’re still not convinced that one of these solutions is right for you, check out our list of the Top RPA Tools of 2021.

The post Blue Prism vs UiPath: RPA Tool Comparison appeared first on IT Business Edge.

Jump to:

• What is Data Analytics?
• What Skills Does a Data Analyst Need?
• Best Data Analytics Certifications
• Why You Need Data Analytics Certifications

What is Data Analytics?

Data analytics broadly refers to the process of consolidating and reviewing raw data to look for patterns and anomalies. In business settings, data analytics helps answer some of the most impactful questions that drive innovation and growth. Data analytics starts with descriptive analytics, which illustrates what’s happening within a system based on a few key indicators. 

Descriptive information is helpful for providing context, but it doesn’t necessarily provide guidance. That’s where predictive analytics comes in. With the aid of machine learning technologies like neural networks and natural language processing, predictive analytics offers insight about what will happen in the future based on historical data.

What Skills Does a Data Analyst Need?

There are a few fundamental skills that all data analysts need to be successful. Perhaps most importantly, data analysts should understand Structured Query Language (SQL) and its counterpart, NoSQL. SQL is the language analysts use to communicate with relational databases, which are the most common among large enterprises. For organizations that use more flexible hierarchies, however, NoSQL is a must.

Similarly, statistical programming languages like R and Python allow analysts to build algorithms and perform operations on large data sets that are more advanced than what Excel can do. Excel is another important skill data analysts should master. Though it’s a somewhat clunky application, Microsoft Excel is unrivaled in the business world for baseline data analysis. 

Non-technical abilities data analysts should continue to develop include communication, problem-solving, and presentation skills. Data analysts provide value to their businesses when they can understand the problems that need to be addressed, translate them into an analytics challenge, and present solutions in a way that the rest of the business can understand. This process requires a combination of soft skills and technical expertise.

Best Data Analytics Certifications

Cloudera Data Platform (CDP) Generalist Certification

The Cloudera Data Platform (CDP) Generalist Certification is the next evolution of Cloudera’s CCP and CCA certifications. This 90-minute exam covers 60 questions that aim to evaluate proficiency with the Cloudera Data Platform. This certification is not role-specific, but Cloudera plans to release a CDP Certified Data Analyst exam in the future. Instead, the CDP Generalist exam tests general knowledge of the platform’s main components, security features, analytic experiences, system requirements, and functions. 

Duration: 90 minutes/60 questions

Cost: $300 USD

Dell EMC Proven Professional Data Science Associate 

Although it’s not platform-agnostic, the Dell EMC Proven Professional Data Science Associate certification focuses more on evaluating your data analysis knowledge and abilities that transcend specific products. This exam specifically tests your practical skills in a Big Data project setting. You’ll be tasked with deploying the data analytics lifecycle, using R to analyze and explore data, operationalizing a data analytics project, and utilizing data visualization techniques.

Duration: 90 minutes/60 questions

Cost: $230 USD

AWS Big Data Specialty Certification

The AWS Big Data Specialty Certification validates your skills with implementing AWS technologies, so it’s best to have a few years of experience on your resume before you start preparing for this exam. You’ll be tested on AWS architectural best practices, Big Data design and maintenance skills, and data analysis automation skills. AWS is one of the largest vendors in the market, so this is a valuable vendor-specific certification to have.

Duration: 170 minutes

Cost: $300 USD

Associate Certified Analytics Professional (aCAP)

The Associate Certified Analytics Professional (aCAP) exam is a highly sought-after certification among data analysts with minimal experience. It’s an independent certification that covers the 7 domains of the analytics process: business problem framing, analytics problem framing, data, methodology selection, model building, deployment, and lifecycle management. You’ll have to submit an application to take the exam before you can do anything else, but the aCAP credential has deep ties to Fortune 100 companies like Apple, Coca-Cola, IBM, American Express, and more.

Duration: 100 questions

Cost: $200 USD for INFORMS members, $300 USD for non-members

SAS Certified Data Scientist 

The SAS Certified Data Scientist program has three credentials: Data Curation Professional, Advanced Analytics Professional, and AI & Machine Learning Professional. You must complete the Data Curation Professional segment and at least one of the other two to earn the Data Scientist certification. However, it’s worth noting that the Advanced Analytics Professional and AI & Machine Learning Professional segments each include three subsequent exams you must complete, so this certification takes longer to earn than the others on this list.

Duration: 90-165 minutes per exam

Cost: $180 USD per exam

IBM Data Science Professional Certificate

Similar to Dell’s certification, IBM’s Data Science Professional Certificate signifies your general data analysis skills rather than any platform-specific knowledge. It’s broken into ten courses that are self-paced, but they will take about 11 months to complete at the recommended pace of 3 hours per week. You don’t need any prior experience or education to sign up for the course, which is ideal if your background is in a different field but you’re looking to switch to data analytics.

Duration: 11 months (recommended)

Cost: $38 USD per month (financial aid available)

Why You Need Data Analytics Certifications

Data analytics certifications establish your credibility in your field. They signal to potential employers that you have the right skills for the job, and they can be used as evidence of growth in your current role if you’re looking for a promotion. Similarly, enterprises use data analytics certifications to identify the most qualified candidates for their open roles. A certification is evidence that a reputable company or institution has co-signed your ability to provide quality business outcomes. 

Read next: Best Data Analytics Tools for Analyzing & Presenting Data

The post Best Data Analytics Certifications 2022 appeared first on IT Business Edge.

Partnering with one of the companies on this list is a significant investment in your company’s future. As such, your choice requires careful consideration to ensure your long-term success. A large part of this decision is subjective, so you should trust your intuition about whether a particular vendor is a good fit. To start, however, we’ve looked at a few distinguishing features for each of the top digital transformation companies on this list to help guide your decision.

What is Digital Transformation?

Digital transformation is a broad IT concept that, in practice, is relative to a business’s unique needs. It’s difficult to pin down a universal definition, but digital transformation generally has the goal of replacing manual processes with digital tools and techniques. Advanced technologies like artificial intelligence (AI), machine learning (ML), cloud computing, and 5G networking are all within the scope of digital transformation.

What is a Digital Transformation Consultant?

A digital transformation consultant (DTC) is a company that will inform and guide the digital transformation process for your organization. There are many different strategies and approaches to digital transformation that can impact your business’s ultimate success, so it’s important to select a DTC that aligns with your core values. 

Some top considerations to keep in mind when evaluating potential digital transformation consultants include the scope of work you’ll need from them and any specialties they may offer. You should also understand their philosophies around the environmental impact of digital technologies, potential productivity gains and losses, and business resilience, as these factors can play a major role in the long-term efficacy of your digital transformation.

Digital Transformation Company Comparison

Jump to:

• Cognizant
• KPMG
• Accenture
• Genpact
• IBM
• Trianz

Cognizant

Back to top

Cognizant offers a range of digital transformation services from strategy to managed services. You can also choose from a few unique offerings like workforce transformation and change management. This variety offers organizations the flexibility to add support in more areas as needed. Additionally, Cognizant’s consulting services use human-centered design principles to make data-driven recommendations in real time. Consultants help you orchestrate numerous moving pieces to ensure the long-term scalability and interoperability of your digital transformation tools.

Distinguishing features

• Full-service digital transformation support
• Flexible pricing model
• Innovative yet accessible and sustainable approach to digital transformation
• Less optimized for global businesses

KPMG

Back to top

KPMG’s services can be broken down into four major areas: audit and assurance, tax and legal, advisory, and private enterprise. Its Powered Enterprise solution for rapid modernization helps organizations make digital transformation a way of business rather than a destination. This methodology is invaluable for businesses that want to remain on the cutting edge of new technologies. KPMG’s digital transformation success stories include the City of Amsterdam, Hong Kong Broadband Network (HKBN), SickKids, Spectris, and Team DSM.

Distinguishing features

• Diverse service offerings
• Global network to support international business operations
• Demonstrated experience with emerging technologies
• Hands-on consulting approach
• Less flexible pricing model

Accenture

Back to top

Accenture’s digital transformation consulting areas include cloud acceleration, data-driven enterprise, intelligent operating models, network-connected services, modern architecture, tech ROI, and orchestration. The company’s digital transformation philosophies focus on optimizing the core of the business rather than implementing surface-level digital solutions. This approach helps organizations stay ahead of digital trends. Prominent Accenture clients include Carnival, H&M Foundation, NASA, and BP.

Distinguishing features

• Special focus on 5G-enabled business operations
• “Engine of growth” mindset that puts financial savings back into technological innovation
• Ecosystem of tech partners including Atlassian, AWS, Google Cloud, ServiceNow, Splunk, Microsoft Azure, and others
• In-depth, easy to understand analytics
• Better for large organizations

Genpact

Back to top

Genpact’s approach to digital transformation is industry-specific, though it offers many of the same capabilities to all types of businesses. These services include augmented intelligence, intelligent automation, artificial intelligence, cloud solutions, customer experience (CX) and employee experience (EX) transformation, business applications, and managed services. The industry-specific approach is compelling because it addresses the unique needs of different types of businesses. Genpact also offers different products based on desired outcomes, whether it’s a roadmap for transformation or data-driven insights.

Distinguishing features

• Solutions delivered via modular platform
• Specialized in AI-powered automation and analytics
• Huge network of technology partners
• Extensive documentation of corporate values and case studies
• Industry-driven approach
• More tech-oriented than business strategy-oriented

IBM

Back to top

IBM is one of the oldest technology companies in the world, and it’s still at the forefront of digital innovation. IBM’s digital transformation consultation services cover analytics, application management, AI, cloud computing, hybrid cloud, cybersecurity, e-commerce, and IT infrastructure. There are also tailored services for specific business needs, like operations, customer experience, marketing, finance, talent management, and supply chain. Digital transformation looks different in each of these areas, so a strategy that captures such nuance can make a significant difference.

Distinguishing features

• Specialized in cloud migration, cloud services, and hybrid cloud infrastructure
• Long-standing reputation for expertise and innovation
• Full-spectrum IT capabilities 
• More tech-oriented than strategy-oriented
• Some customers have warned about complicated contracts with lots of loopholes

Trianz

Back to top

Trianz’s digital transformation expertise fills the need that exists at the intersection of data, people, technology, and business priorities. Rather than taking a siloed approach to these digital transformation elements, Trianz takes a holistic approach and offers key competencies for cloud platforms, data and analytics, digital experiences, digital applications engineering, IT infrastructure management, and cybersecurity. Trianz also uses a digital transformation benchmarking model that helps organizations visualize where they are, where they want to be, and the steps that need to be taken to bridge that gap.

Distinguishing features

• Emphasis on post-digital KPIs
• Unique digital studio for people-centric digital transformation design
• Human-oriented design principles that are adaptable and easy to understand
• Clear vision of data-driven digital transformation pathways and success metrics

How to Choose the Right Digital Transformation Consultant

Aside from the distinguishing features we’ve listed here, it’s worthwhile to spend some time diving deeper into each digital transformation consultant’s published research and case studies. This can give you considerable insight into their methodologies and approaches to specific problems as well as the kinds of outcomes you can expect for your own challenges. 

Ultimately, the right digital transformation consultant for your organization is largely a subjective choice. You can compare the service offerings and fee structures of the top choices we’ve listed here, but if you feel that a potential consultant may not align with your priorities or may be difficult to work with, then it’s not the right fit. The resource and financial investment that comes with a digital transformation consultant is not small, so the best choice will offer high-quality service and a true partnership for your organization.

Read next: Emerging Technologies are Exciting Digital Transformation Push

The post Top Digital Transformation Companies & Services 2022 appeared first on IT Business Edge.

Top Cloud Provider Comparison

• Amazon Web Services: Best for availability
• Microsoft Azure: Best for ease of use
• Google Cloud Platform: Best for analytics
• Alibaba Cloud: Best for pricing flexibility

Amazon Web Services: Best for availability

Amazon Web Services (AWS) has led the cloud IaaS market for many years, and it’s easy to understand why. AWS offers more services and features than any other cloud service provider, and it offers higher availability than most of its competitors. In fact, the AWS infrastructure has 81 Availability Zones in 25 regions around the world and guarantees a 99.99% uptime. 

AWS also offers a lot in the way of cybersecurity. It supports 90 security standards and compliance certifications and offers encryption for any service that interacts with customer data. AWS is a one-stop shop for virtually any cloud service, so it’s a clear choice for organizations needing versatility and advanced solutions.

Pros

• Limitless server capacity
• Flexible scalability
• Broad toolset
• Straightforward user interface

Cons

• Complicated pricing structure
• Difficult to manage costs effectively

Pricing

Though AWS is the leader of the cloud services market, its pricing structure is anything but straightforward. Though it does offer a pricing calculator, it can be hard to estimate exactly how much the services will cost because of how many different variables there are. However, AWS is one of the most affordable cloud solutions available. Plus, the Free Tier includes more than 100 products that can be expanded and scaled as needed. 

Read more: AWS Extends Scope of Cloud Storage Services

Microsoft Azure: Best for ease of use

Microsoft has long been a leader in the on-premises software market, so it makes sense that they were able to gain momentum quickly when they pivoted to cloud services with Azure. Plus, Azure was designed to work in tandem with other Microsoft products like Windows Server and Microsoft Office. This is a huge benefit for enterprises that are already using Microsoft tools. 

The breadth of solutions Azure offers isn’t as wide as AWS, and the products it does offer usually come with a bigger price tag than its competitors. However, Azure is one of the easiest cloud solutions to set up and manage. It supports Linux systems and container architectures, which is a unique value for open source environments.

Pros

• Integrates with other Microsoft products
• Supports Linux and container architectures
• User friendly
• Good for hybrid cloud environments

Cons

• More expensive than AWS
• Poorer performance than competitors

Pricing

Microsoft Azure’s pricing is also somewhat convoluted. The pay-as-you-go structure is based on a number of situational variables, so it’s difficult to understand how much the services will cost before committing. Azure offers a small number of services on a forever free basis, plus its most popular services on a 12-month free trial. On average, however, Azure costs more to deploy than AWS.

Read more: Azure Stack vs. Azure Cloud: Private vs. Public Cloud

Google Cloud Platform: Best for analytics

Google Cloud Platform (GCP) is the third most popular cloud service provider behind AWS and Azure. Though its track record with enterprise customers is relatively short, it does have a unique advantage over its competitors when it comes to analytics, automation, and networking. GCP’s artificial intelligence and machine learning tools are some of the most advanced of any in the cloud computing space.

Many customers choose to use GCP as a supplementary cloud service in a multi-cloud environment. Its live migration feature is useful for these customers because it enables VM migration in real time without any downtime. Additionally, Google’s Kubernetes framework is the foundation for most container environments, so GCP is an ideal solution for containerized app development. GCP might not be the biggest cloud provider on the market, but it’s growing rapidly and driving innovation on many fronts.

Pros

• Live migration
• Unparalleled data analytics
• Accessible customer support
• Good for multi-cloud environments

Cons

• More expensive than AWS
• Lower availability

Pricing

Google Cloud may be more expensive than AWS, but its pricing structure is more transparent. It offers a pricing calculator to understand exactly what costs to expect based on a number of variables using the pay-as-you-go pricing model. Google offers deep discounts and flexible contracts to draw customers from other cloud providers. There are also special tools and support channels to optimize costs.

Alibaba Cloud: Best for pricing flexibility

Alibaba Cloud is the top cloud service provider in China, so it’s a likely choice for enterprises with a large presence in the APAC region. However, Alibaba has rapidly expanded its reach to become a major competitor around the globe. It has a more flexible pricing structure than most providers, plus new customers can take advantage of Alibaba’s free trial to test drive the most expensive products before committing.

The interface is not very intuitive for users who don’t have strong technical expertise, but there is decent multilingual support and an energetic community of users who are willing to collaborate to solve a problem. Though their presence in Western markets is relatively small, Alibaba Cloud is perhaps one of the most affordable, fastest growing, and most internationally-friendly cloud providers on the market.

Pros

• Impressive free trial offering
• Strong presence in APAC
• Flexible pricing options
• Multilingual support

Cons

• Requires technical expertise
• Limited geographical availability outside APAC

Pricing

Alibaba Cloud’s services are priced using the pay-as-you-go model or subscription billing for a lower monthly rate. There are no upfront fees, so there’s very little cost to get started, and many services are available for free. Alibaba also offers a referral program that provides discounts to customers who invite colleagues or partners to join Alibaba Cloud. 

Read more: Alibaba Cloud vs. AWS

How to Choose the Right Cloud Provider

It can be difficult to determine which top cloud provider is the right fit for your organization. First, understand your top business priorities and read customer reviews from those with similar needs. Then, consider signing up for a free trial or exploring some of the tools each provider offers for free to get a sense of how the services work. 

If none of the top cloud providers on this list meet your needs exactly, review our complete list of Top Cloud Providers & Companies to explore other options.

The post AWS vs Azure vs Google vs Alibaba: Compare Top Cloud Providers appeared first on IT Business Edge.

You can use Ping Identity to create seamless and secure sign on experiences for your customers and employees alike, but how do you know if it’s the right fit for your organization? Consider your needs while reading our overview of Ping Identity’s features and pricing.

Jump to:

• Ping Identity Features
  • Register
  • Verify
  • Authenticate
  • Authorize
  • Monitor
• Ping Identity Pricing

Ping Identity Features

Ping Identity can be tailored specifically for customers, partners, and employees. However, the platform as a whole includes a few core features that help register, verify, authenticate, authorize, and monitor all users across your entire system.

Register

Ping Identity functions as a federation hub to provide SSO capabilities across multiple service and identity providers. It supports a number of different standards including OpenID Connect, OAuth, SAML, WS-Federation, WS-Trust, and SCIM among others. Then, the Ping Identity directory aggregates identity and profile data from a variety of technologies, encrypts it, and protects it from external and insider attacks.

Verify

The identity verification features embedded in the Ping Identity platform are relatively straightforward. Each new user is required to submit a copy of their photo ID and a photo captured in real time using their device’s camera. This information is then cross-referenced to confirm that each user is who they claim to be. 

If a user needs to create additional accounts, Ping Identity registers their identity details with their device so they don’t have to go through the verification process again. This improves the user experience on the front end and prevents duplicate records on the back end.

Authenticate

An MFA feature is a must-have for any viable IAM platform, but Ping Identity takes it one step further. Ping uses adaptive authentication, which takes into consideration the user’s contextual and behavioral details like geolocation and the length of time since they last logged in. Adaptive authentication adds an extra layer of security to keep unrecognized users out while also making access easier and safer for legitimate users. 

Furthermore, Ping Identity supports passwordless authentication. This cutting edge technology altogether eliminates one of the biggest security vulnerabilities: weak passwords. Instead, Ping uses advanced authentication mechanisms to create a stronger yet simpler login experience. 

Authorize

Once registered users have been verified and authenticated, Ping Identity then allows you to authorize users for the appropriate levels of access to your systems. Authorization controls are crucial for compliance with consumer data regulations, and Ping offers dynamic authorization to make context-driven access decisions in real time. The fine-grained attribute-based access controls are precisely what enterprises need to maintain agility while also preserving compliance.

Monitor

Last but certainly not least, Ping Identity offers multiple monitoring features including risk management, API security, fraud detection, and orchestration. All of these tools work together to keep a constant watchful eye on the system’s risk signals from top to bottom. In the long run, these help create a frictionless user experience and a proactive security framework without creating more work for your IT staff.

Ping Identity Pricing

Ping Identity does not provide pricing for its software upfront. Instead, the Ping sales team creates custom packages based on each customer’s unique needs for customer and workforce identity access management. Ping does provide access to a free trial without requiring any credit card details, so it’s an easy way to get a first-hand look at the platform without needing to speak to a sales rep first.

How to Choose the Best IAM Software

There are many IAM software vendors that suit a variety of different needs. If you’re looking for a solution that can help you manage your customer or employees identity data with cutting-edge authentication features, Ping Identity might be the best fit for you. If you’re still exploring your options, however, our list of the Best IAM Solutions & Tools may be able to help.

The post IAM Software: Ping Identity Overview & Pricing appeared first on IT Business Edge.

The trends that are expected to take hold in 2022 don’t necessarily signify the need for enterprises to overhaul their DX strategies. Instead, these trends are an understanding of the challenges and opportunities to come. Most of them have long loomed on the horizon, but recent challenges with supply chain, security, and other business priorities have spurred notable growth that will shift digital transformation perspectives in the coming year.

Top Digital Transformation Trends for 2022

• Automation will power prescriptive guidance
• Agility will become a bigger priority
• Low-code tools will become mainstream
• Just-in-time analytics will address the supply chain crisis
• Data will become the backbone of customer experience
• IT budgets will increase

Automation will power prescriptive guidance

Analytics have powered much of the innovation of the last decade. It tells us what happened, explains why it happened, and predicts what will happen in the future. When combined with automation, we can move past descriptive and predictive analytics toward prescriptive guidance.

“Artificial intelligence combined with automation will finally make this possible by dynamically combining relevant data and alerting knowledge workers to take action, in advance, before an event occurs,” says Ashley Kramer, chief product officer and chief marketing officer at Sisense. You can leverage analytics to understand what’s happening in your system at any given time, then combine this information with automation to get intelligent recommendations. In the long run, this will help you make better decisions for your organization.

Kramer continues by describing how this can impact different business units in specific ways:

“Customer service reps will be notified to reach out to potentially angry customers before they even call in. Sales leaders can react immediately to dips in revenue pipeline coverage due to upstream activities without waiting until the end of the quarter. Retail managers can optimize inventory before items sell out by combining more than just sales data, such as purchasing patterns of other items, external market trends, and even competing promotional campaigns.”

With traditional analytics, we can only understand what’s happening in the moment and make an educated guess at what will happen next. Analytics augmented by automation, on the other hand, gives us a solid foundation on which we can plan for the future.

Read more: The Growing Relevance of Hyperautomation in ITOps

Agility will become a bigger priority

If the Colonial Pipeline attack taught us anything in 2021, it’s that ransomware attacks are becoming a more serious threat than ever before. Along the same lines, we also learned that a business’s agility is the key to its survival in catastrophic circumstances. 

To that end, Ginna Raahauge, CIO at Zayo, says enterprises should prioritize their investments in disaster recovery and business continuity. She explains, “Agility to me translates at the lowest level to dynamic coverage or dynamic recovery. Companies will want to get to a point where they’re not preparing for ‘what if’ scenarios, but that they have real actionable steps in mind that are dynamic and will prevent them from suffering through any outages.”

It’s not a matter of estimating the likelihood that your organization will become the victim of a security incident, but rather what you’ll do when that inevitably happens. Of course, this takes a tremendous amount of effort to consider the necessary preparations from every angle. Work with stakeholders in your organization to ensure all of your bases are covered, but don’t forget the systems outside of your direct purview as well. 

“From a network perspective,” Raahauge says, “agility will be key as well: ensuring you have infrastructure partners with diverse routes to ensure business continuity as you move to more cloud-based structures.” Digital transformation is about having the right technology solutions in place, but it’s also about being prepared to keep the business afloat when those solutions fail.

Read more: Best Business Continuity Management (BCM) Software

Low-code tools will become mainstream

More enterprises will also see a shift toward low-code or no-code software adoption. These tools have long been the source of some controversy in the IT industry because many developers have feared their jobs would become obsolete if companies could operate on low-code software alone. However, this category of tools has proven to be an asset to developers in recent years.

“No-code tools are great to solve simpler problems,” says Dean Guida, CEO and founder of Infragistics. “When you combine low-code tools and professional developers you can tackle the higher impact digital solutions that will give competitive advantage to organizations.” 

Low-code and no-code software means developers can prioritize innovation and business growth rather than spending time building tools for day-to-day operations. But that’s not where the benefits stop. Low-code solutions also provide an opportunity for professionals in other parts of the organization to make smarter decisions without confronting a steep learning curve. 

Francois Laborie, President of Cognite North America, understands why the accessibility of data-driven software is so important. “You need technology that makes working with data intuitive for a large group of users,” he says. “The data presented to any unit of a company needs to be contextualized and reliable, so individuals can identify problems sooner and make more informed decisions quickly. The winners in the industrial DX race will be those who provide these tools to their people at speed.” 

As day-to-day business operations become more reliant on good data, the tools that engage with that data will become equally valuable. Low-code software fills in the gap between what the broader business needs to keep the lights on and what developers need to focus on to keep driving the business forward.

Read more: Democratizing Software Development with Low-Code

Just-in-time data analytics will address the supply chain crisis

Another challenge most enterprises have faced in the past year? Supply chain disruptions. Whether it’s inventory shortages or shipping delays, significant supply chain challenges have sent organizations of all sizes in all industries scrambling. Many experts anticipate that data analytics will be the solution.

Matthew Halliday, co-founder and executive vice president of product at Incorta, explains that data analytics need to be applied to the supply chain to effectively deliver on a “just in time” strategy: 

“Faced with a full-blown supply chain crisis, companies will have to address long standing issues in their data pipelines—bottlenecks and other fragilities—that prevent teams from gaining the visibility into supply chains they need to survive the decade. No longer held back by the gravity of legacy models, systems and approaches, companies will embrace innovative new solutions in a bid to make ‘just-in-time’ data analytics a reality for their business.”

Data will become the backbone of customer experience

The COVID-19 pandemic has hastened yet another facet of digital transformation: data-driven approaches to customer experience. When the onset of the virus forced the world into lockdown, many businesses looked for new ways to reach customers without risking exposure. Social media, ecommerce, and other digital marketing channels became the champions of staying connected during the pandemic.  

However, it quickly became clear that the mere availability of new channels was not enough. Customers wanted the same kind of personalized experiences they were used to in face-to-face interactions, not a one-size-fits-all approach. Neal Keene, Field CTO at Smart Communications, rightly believes that organizations should leverage customer data to create this level of personalization.

“It’s no longer good enough to just be available for customers anymore,” Keene says. “Instead, businesses need to take this baseline and go one step further by leveraging technology to provide more streamlined and personalized engagement with their customers. This means doubling down on digital to enable two-way conversations with customers. It also means tapping into data insights to ensure that each touchpoint is specifically tailored to each individual customer’s needs and expectations.” 

Customers effectively want the same experience when interacting with a business whether they choose to do so online or in person. To meet this demand, organizations should have a clearly defined omni-channel strategy and a consolidated, streamlined view of their customer data. Big data analytics platforms like Tableau and Apache Spark can aid in this effort.

Read more: Best Big Data Tools & Software for Analytics

IT budgets will increase

With all of these trends knocking at the door of digital transformation in 2022, it makes sense that most enterprises’ IT budgets will increase as well. This prediction is in line with Gartner’s forecast that worldwide IT spending will reach $4.5 trillion by this time next year — a 5.5 percent increase over 2021. 

The largest motivation for this increase is the expectation that more organizations will shift from buying and implementing third-party software to building any high-level software needs in-house. This shift is also understandable considering how specialized each organization’s IT needs are becoming. 

With the exception of low-code and no-code tools, many top-tier software solutions require a significant amount of time, money, and effort to implement. Even then they might not check every box. Developing a fully customized tool from the ground up is often the path of least resistance, though it often comes with a bigger price tag. 

As the new year approaches, enterprises should consider how innovative IT solutions can support their broader priorities. Digital transformation allows businesses to become more agile, productive, and dynamic in almost every aspect of their organization when implemented strategically. For the best possible outcomes, businesses should align their IT budgets with these priorities.

Read next: 5 Digital Transformation Hurdles and How to Get Over Them

The post Top 6 Trends Shaping Digital Transformation in 2022 appeared first on IT Business Edge.

DevOps Trends for 2022

• Shift toward serverless computing
• Microservices architecture growth
• Kubernetes as a development framework
• Rise of DevSecOps
• Low-code application adoption

Shift toward serverless computing

Serverless computing is an emerging trend that’s actually been around for more than a decade. It’s taken a while for enterprises to buy into the serverless framework, mostly because of fear: fear around industry support and fear about the return on investment. However, serverless comes with many advantages that are becoming increasingly difficult to ignore.

The two biggest benefits of serverless computing are efficiency and reliability. Without the burden of infrastructure management, enterprises can focus their resources on bigger priorities. Plus, serverless relieves the risk of potential maintenance issues that can occur with traditional frameworks.

Michelle Gienow, technical sourcer at Cockroach Labs, predicts serverless will experience its next evolution in 2022. “The evidence of how serverless benefits the enterprise has become overwhelming,” she says, “and products supporting and easing serverless adoption are proliferating. We think serverless will eventually become just an implementation detail, providing inherent scalability and reliability — and automating routine operational tasks that few developers enjoy.”

Also read: Is Serverless Computing Ready to Go Mainstream?

Microservices architecture growth

Microservices go hand-in-hand with serverless computing. With this concept, applications are broken into independent units, thereby giving large teams more flexibility. Developers can access a wide range of tools using whatever programming language or database they need. The confines of traditional app development are completely removed.

When implemented successfully, microservices also offer enterprises better scalability and agility than monolithic applications. Developers can scale each segmented service according to the business’s needs rather than trying to scale an entire application at once. Additionally, if something goes wrong, microservices make it easy to contain the problem without disrupting the whole application.

As serverless computing gains momentum in 2022, so will microservices. However, it’s worth noting that microservices growth will be slower among smaller companies. The risk of poor microservices implementation can come with a long list of complications, including data loss, poor reliability, and security risks. 

Kubernetes as a development framework

Kubernetes is the third ingredient in the serverless/microservices development cocktail that’s expected to take off in 2022. Kubernetes, also called K8s, is a type of microservices software that enables container orchestration. It’s been an emerging infrastructure trend for a few years, but experts anticipate that it will expand further into the software development realm in the coming year. 

Nicholas Benjamin, Nintex’s senior vice president of engineering, is particularly excited about the continued adoption of Kubernetes. “It’s now regarded, I think, as the de facto standard for container orchestration, but I think we’ll continue to see it evolve from organizations treating it as almost pure ‘ops’ capability (i.e., an easy way to provision and manage infrastructure) to more of an ‘app’ developer capability, where it’s jointly loved and owned by Software and DevOps engineers,” he says.

Rise of DevSecOps

Security is becoming another rising concern in the DevOps sector, and it’s easy to understand why. As cloud computing becomes more readily accessible, new security threats seem to be around every corner. That’s why DevSecOps is becoming a bigger part of many companies’ org charts.

ServiceNow’s senior director of DevOps product management, Anand Ahire, expects this shift to happen naturally. “We’ve seen a rapid increase in [DevSecOps] adoption as companies focus more on shifting security left (having largely solved the automated testing problem),” he explains. “The future direction for DevSecOps will tie the build-phase scanning that we see in DevOps today with Security Operations work that happens in the operational phase. DevSecOps and SecOps will become one larger discipline.”

Tim Johnson, senior product marketing manager at CloudBees, thinks of DevSecOps a bit differently: “The executive orders and tighter integration of security and compliance tools with the software delivery supply will result in the concept of DevSecOps — a separate thought process or practice that adds security thinking and actions to DevOps — dying a quiet death.” He clarifies by saying that “doing DevOps right means that security is an integral component of all stages of the process.”

Also read: Shift Left DevOps Security Approach & Tools

Low-code application adoption 

Last but not least, the majority of development environments are expected to adopt low-code software by the end of 2022. Low-code tools are somewhat controversial in the DevOps community, but they’ve proven to be an asset to developers’ productivity.

Developers often feel that low-code applications threaten their job security, but ServiceNow’s Marcus Torres, GM of IntegrationHub and VP of Platform Product, strongly believes that these tools help developers more than hurt them. He explains that “developers like using no-code/low-code tools to get past what I want to call the remedial part of application development and really focus on the challenging parts.”

The productivity boost is what will cause more developers to lean into the low-code trend in 2022. Steven Jefferson, senior advisory solution consultant at ServiceNow, envisions a software development process that includes more low-code tools. “As the low-code adoption matures,” he says, “we’ll see it expanding to support the entire software development cycle. In this phase, low-code solutions will cover every aspect of software development in a simpler way across app ideation, solution design, development, user testing, release management, documentation, and more.” 

Low-code solutions will allow developers to focus on the bigger picture, whether it’s DevSecOps, Kubernetes, microservices, or serverless computing.

Read next: 5 Emerging Cloud Computing Trends for 2022

The post Top DevOps Trends to Watch in 2022 appeared first on IT Business Edge.

Both options offer unique advantages and disadvantages, but neither is a one-size-fits-all solution. To determine which one is best for your business, keep your unique needs in mind while comparing the pros and cons of both ITSM tools.

Jump to:

• ServiceNow vs. Salesforce: Features
• ServiceNow vs. Salesforce: Implementation
• ServiceNow vs. Salesforce: Pricing

ServiceNow vs. Salesforce: Features

ServiceNow was specifically developed to help IT operations teams work more efficiently. As such, it has all the right features to create a single system of record and automate the service management process. Salesforce, on the other hand, was not developed for ITSM specifically, but it is one of the most versatile and flexible CRM tools on the market. Therefore, it can be customized to meet many ITSM needs while also prioritizing the sales pipeline.

Salesforce features

Salesforce’s ITSM product, called Service Cloud, is a popular cloud-based tool for service desk needs. It lacks many of the standard ITSM capabilities like asset management or change management, but it does offer a few powerful features at the intersection of ITSM and CRM. For example, the visual remote assistant feature allows service representatives to improve the troubleshooting experience. Additionally, the incident management feature uses artificial intelligence to identify patterns based on incoming cases, then provides high level information to help proactively address underlying issues.

It’s worth noting that anything that cannot be accomplished by Service Cloud independently can likely be accomplished with a third-party integration. Because Salesforce is such a popular platform, most top software solutions seamlessly integrate with all Salesforce products, including Service Cloud. This has the benefit of being a more customizable solution. However, a dedicated ITSM feature will offer more of these features straight out of the box, so you won’t need to spend as much time fussing with configurations.

ServiceNow features

ServiceNow is a purpose-built ITSM product. In fact, it was our pick for the best overall ITSM software. It has a full suite of ITSM features, including discovery, service mapping, cloud management, and orchestration. Its operational intelligence capabilities use AI to automate incident management, change management, configuration management, and service desking processes. When all of these features work in unison, ServiceNow becomes an ITSM force to be reckoned with.

ServiceNow is also a codeless solution, which means it doesn’t require as much configuration time as Salesforce does. It still takes some time to get it up and running, but compared to other solutions, it’s a relatively low-maintenance solution. Best of all, it integrates with other business-critical applications to provide a single system of record for all IT needs.

ServiceNow vs. Salesforce: Implementation

Both ServiceNow and Salesforce can take a long time to implement, though Salesforce often takes more time to configure and customize to meet the business’s needs. Both solutions also require a dedicated administrator to coordinate support needs and maximize the value of each platform — for the most part, they’re too advanced for average users without some degree of technical expertise. 

It’s also important to point out that Salesforce implementation specifically requires a significant amount of strategy and planning. Without the right controls in place, the system can accrue a large amount of technical debt that can cause major headaches down the line. Having a strategy in place will ensure the business will be set up for success long-term, but it also means ServiceNow might be a better solution if you need something to get up and running more quickly.

ServiceNow vs. Salesforce: Pricing

Another significant difference between ServiceNow and Salesforce is that Salesforce offers much more transparent pricing. There are four different Salesforce Service Cloud packages:

ServiceNow, on the other hand, doesn’t disclose any of its pricing upfront. Each customer gets a customized price based on their feature and licensing needs. This means ServiceNow is somewhat more flexible than Salesforce, but more difficult to compare cost-wise while doing preliminary research. Most users report their monthly ServiceNow costs starting around $100, so Salesforce might be a more affordable option for less advanced needs.

To compare these contenders with other ITSM software solutions, check out our list of Top ITSM Tools & Software.

The post ServiceNow vs Salesforce: ITSM Tool Comparison appeared first on IT Business Edge.

Matt Fairhurst, CEO of Skedulo, knows this better than most—his company’s deskless productivity platform uses AI to help businesses optimize their workforces. The platform’s AI and machine learning feature, called MasterMind, focuses on the priorities and variables that matter most to businesses, including workforce utilization rate, operating cost, travel time, and more. 

Fairhurst spoke with IT Business Edge about AI in the job market, the risks of AI integration in software development, and how Skedulo has used AI to transform the mobile workforce. 

Also read: How Machine Learning Shapes Artificial Intelligence Technologies

How AI Is Augmenting the Mobile Workforce

Artificial intelligence is often talked about as the future replacement for human intelligence. AI is a long way away from taking over for humans, but it has started helping humans in the workplace. Across all industries, AI helps workers spend less time doing repetitive, menial tasks and more time looking at the bigger picture. 

Some industries are more inclined toward automation than others. As Fairhurst puts it, “Relative to industries such as financial services or high-tech, field service isn’t as innovative. Despite the hype of AI, adoption has been relatively slow. We estimate that 20-30% of field service jobs currently rely on some type of AI, but adoption is definitely accelerating.”

Field service workers might not be the first in line to adopt AI technology as part of their roles, but that doesn’t mean they’re completely left out of the conversation. Many analog businesses are looking to adopt AI software as the first step on their digital transformation journey. 

“We’re seeing more and more traditional businesses hire full-time software developers to stay competitive. It’s a great time to be a developer — demand for digital transformation solutions has never been higher,” says Fairhurst.

Risks of Integrating AI With Software Development

AI integration in any field is not without its risks. Security and privacy are major concerns, but so is the longevity of such an advanced technology. To this end, Fairhurst explains that companies wanting to dip their toes in the AI waters will likely face an uphill battle.

“One of the biggest risks with AI software development is its long-term viability,” he says. “AI is very sophisticated and oftentimes a very delicate type of software, and it’s hard enough to get it working, let alone keep it working over the long haul.”

Long-term strategy is key to AI software development and implementation. It may be tempting to do things that will save time and money, but that could have disastrous consequences in the long run. 

“To ensure success over the long term,” Fairhurst says, “businesses need to be particularly planful and avoid cutting corners during development. Rushing to market with half-baked technology in this space will be disastrous.” 

Failure to plan adequately could ultimately cause more delays and cost more money, so it’s important to focus on fine-tuning the details rather than implementing the software before it’s ready.

Also read: What is Artificial Intelligence as a Service (AIaaS)?

The Role of AI in Skedulo’s Software

According to research from Skedulo, 58 percent of deskless workers feel their job has become more difficult since COVID-19, and 86 percent of IT executives claim worker productivity is negatively impacted by their existing technology. Only a slim segment of the software industry focuses on addressing the needs of deskless workers, which is entirely disproportionate to the majority (80 percent) of workers who are not in a traditional office setting. 

To confront this challenge, Skedulo is consistently looking for new ways to help the deskless workforce leverage the impact of artificial intelligence. The most recent innovation has come in the form of MasterMind Solvers, which are scenario-specific optimization algorithms that address the inefficiencies deskless workers often face. Like other AI-based applications, Skedulo’s machine learning capabilities reveal patterns and trends that help businesses automate repetitive tasks.

Furthermore, Fairhurst describes the MasterMind enhancements as a way for organizations to make smarter and faster scheduling decisions based on user-defined variables. “MasterMind Solvers enable users to easily rank scheduling variables by importance and automate schedules accordingly,” he says. “This can significantly reduce travel time, distance, and cost per hour for deskless workers and organizations while maximizing work capacity, increasing workforce utilization, and best matching worker and job attributes.”

Artificial intelligence and machine learning features in solutions like Skedulo help businesses make their day-to-day operations more efficient. As nearly every industry is discovering the power of automation and smart technologies, it’s becoming clear that organizations closed off to these innovations will likely be left behind.

The post Q&A with Skedulo: How AI is Shaping Software Development appeared first on IT Business Edge.