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Experts Blog: Boris Evelson

Content syndicated from Forrester.com
Boris has more than 25 years of experience with enterprise software and applications implementation, management consulting, and strategic advisory skills.
  • Agile, flexible, modern BI deployments often require help from the professionals

    Digitally empowered customers -- both businesses and consumers -- wield a huge influence on enterprise strategies, policies, and customer-facing and internal processes. With mobile devices, the Internet, and all-but-unlimited access to information about products, services, prices, and deals, customers are now well informed about companies and their products, and are able to quickly find alternatives and use peer pressure to drive change. But not all organizations have readily embraced this new paradigm shift, desperately clinging to rigid policies and inflexible business processes. A common thread running through the profile of most of the companies that are not succeeding in this new day and age is an inability to manage change successfully. Business agility -- reacting to fast-changing business needs -- is what enables businesses to thrive amid ever-accelerating market changes and dynamics.

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  • Salesforce.com Enters The BI Market With Wave, The Salesforce Analytics Cloud

    There just might be another 800-lb gorilla in the Business Intelligence market. In a year.

    The popular cult book "Hitchhiker's Guide To The Galaxy" by Douglas Adams defines space as ". . . big. Really big. You just won't believe how vastly, hugely, mind-bogglingly big it is. . ." There are no better words to describe the size and the opportunity of the business intelligence market. Not only is it "mind-bogglingly big," but over the last few decades we've only scratched the surface. Recent Forrester research shows that only 12% of global enterprise business and technology decision-makers are sure of their ability to transform and use information for better insights and decision making, and over half still have BI and analytics content sitting in siloed desktop-based shadow IT applications that are mostly based on spreadsheets.

    The opportunity has provided fertile feeding ground to more than fifty vendors, including: full-stack software vendors like IBM, Microsoft, Oracle, and SAP, each with $1 billion-plus BI portfolios; SAS Institute, a multibillion BI and analytics specialist; popular BI vendors Actuate, Information Builders, MicroStrategy, Qlik, Tableau Software, and Tibco Software, each with hundreds of millions in BI revenues; as well as dozens of vendors ranging from early to late stage startups.

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  • The Good The Bad And The Ugly Of Enterprise BI

    Unified information architecture, data governance, and standard enterprise BI platforms are all but a journey via a long and winding road. Even if one deploys the "latest and greatest" BI tools and best practices, the organization may not be getting any closer to the light at the end of the tunnel because:
    • Technology-driven enterprise BI is scalable but not agile. For the last decade, top down data governance, centralization of BI support on standardized infrastructure, scalability, robustness, support for mission critical applications, minimizing operational risk, and drive toward absolute single version of the truth -- the good of enterprise BI -- were the strategies that allowed organizations to reap multiple business benefits. However, today's business outlook is much different and one cannot pretend to put new wine into old wine skins. If these were the only best practices, why is it that Forrester research constantly finds that homegrown or shadow BI applications by far outstrip applications created on enterprise BI platforms? Our research often uncovers that -- here's where the bad part comes in -- enterprise BI environments are complex, inflexible, and slow to react and, therefore, are largely ineffective in the age of the customer. More specifically, our clients cite that the their enterprise BI applications do not have all of the data they need, do not have the right data models to support all of the latest use cases, take too long, and are too complex to use. These are just some of the reasons Forrester's latest survey indicated that approximately 63% of business decision-makers are using an equal amount or more of homegrown versus enterprise BI applications. And an astonishingly miniscule 2% of business decision-makers reported using solely enterprise BI applications.
    • Read more
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  • Lost In Data Translation? Forrester's Data Taxonomy To The Rescue

    • When it comes to data technology, are you lost in translation? What's the difference between data federation, virtualization, and data or information-as-a-service? Are columnar databases also relational? Does one use the same or different tools for BAM (Business Activity Monitoring) and for CEP (Complex Event Processing)? These questions are just the tip of the iceberg of a plethora of terms and definitions in the rich and complex world of enterprise data and information. Enterprise application developers, data, and information architects manage multiple challenges on a daily basis already, and the last thing they need to deal with are misunderstandings of the various data technology component definitions.
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  • Agile BI Ship Has Sailed — Get On Board Quickly Or Risk Falling Behind

    The battle over customer versus internal business processes requirements and priorities has been fought -- and the internal processes lost. Game over. Customers are now empowered with mobile devices and ubiquitous cloud-based all-but-unlimited access to information about products, services, and prices. Customer stickiness is extremely difficult to achieve as customers demand instant gratification of their ever changing needs, tastes, and requirements, while switching vendors is just a matter of clicking a few keys on a mobile phone. Forrester calls this phenomenon the age of the customer. The age of the customer elevates business and technology priorities to achieve:

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  • Forrester's 10-Step Methodology For Shortlisting Business Intelligence Vendors

    BI is no longer a nice-to-have back-office application that counts widgets -- it is now used as a key competitive differentiator by all leading organizations. For decades, most of the BI business cases were based on intangible benefits, but these days are over -- today 41% of professionals, with knowledge of their firm's business case, base their business case on tangible benefits, like an increased margin or profitability. As a result, BI is front and center of most enterprise agendas, with North American data and analytics technology decision-makers who know their firm's technology budget telling Forrester in 2014 that 15% of their technology management budget will go toward BI-related purchases, initiatives, and projects.

    But taking advantage of this trend by deploying a single centralized BI platform is easier said than done at most organizations. Legacy platforms, mergers and acquisitions (M&A), BI embedded into enterprise resource planning (ERP) applications, and organizational silos are just a few reasons why no large organization out there has a single enterprise BI platform. Anecdotal evidence shows that most enterprises have three or more enterprise BI platforms and many more shadow IT BI platforms.

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  • A common denominator for pricing and negotiating Business Intelligence (BI) and Analytics software

    BI and analytics software packaging and pricing are a Wild West with few common practices among the vendors. Comparing and contrasting vendor prices and negotiating with vendors is challenging because

    • Few vendors publish list prices, so when a vendor tells you you are getting a certain discount you can't really verify whether the discount numbers are valid or not.
    • Vendors base their prices on multiple variables such as
      • Total number of users
      • Concurrent users
      • User types
      • Connectivity to certain types of data sources
      • Number of CPU cores or sockets
      • CPU clock speed
      • Amount of RAM
      • Server Operating System (OS)
      • Environments such as development, test, QA (quality assurance), UAT (user acceptance testing), production, and DR (disaster recovery)

    So how do you know if you are getting a good deal? Here's a best practice and a few price ranges you can use to get you started. First of all, at the end of the day, it's the number of users and user types that are always a common denominator regardless of BI software platform or your particular implementation. Consider the following price ranges for specific user types

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  • What Do Business Intelligence Consultants Mean By “Solutions”?

    Management consultants and business intelligence, analytics and big data system integrations often use the terms accelerators, blueprints, solutions, frameworks, and products to show off their industry and business domain (sales, marketing, finance, HR, etc) expertise, experience and specialization. Unfortunately, they often use these terms synonymously, while in pragmatic reality meanings vary quite widely. Here's our pragmatic take on the tangible reality behind the terms (in the increasing order of comprehensiveness):

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  • What does Business Intelligence integration with R really mean

    "A little prediction goes a long way" wrote Eric Siegel in his popular Predictive Analytics book. True, predictive analytics is now part and parcel of most Business Intelligence (BI), analytics and Big Data platforms and applications. Forrester Research anecdotal evidence finds that open source R is by far the most ubiquitous predictive analytics platform. Independent findings and surveys like the ones by KDNuggets and RexerAnalytics confirm our conclusions (and I quote) "The proportion of data miners using R is rapidly growing, and since 2010, R has been the most-used data mining tool. While R is frequently used along with other tools, an increasing number of data miners also select R as their primary tool."

    To jump on this R feeding frenzy most leading BI vendors claim that they "integrate with R", but what does that claim really mean? Our take on this - not all BI/R integration is created equal. When evaluating BI platforms for R integration, Forrester recommends considering the following integration capabilities:

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  • [Poll] What does the term Business Intelligence (BI) mean to you and your organization?

    * BI = reporting, querying, OLAP
    * BI = all of the above + data visualization / dashboards
    * BI = all of the above plus analytics (advanced, predictive)
    * BI = all of the above + Big Data
    * BI transforms data into info to improve biz performance. It's an uber concept that encompasses all of the above + data mgmt

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