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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.
  • 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.
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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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  • The Forrester Wave™: Enterprise Business Intelligence Platforms, Q4 2013

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  • How To Have The BI Cake And Eat It Too: A (Or The) BI Prediction For 2014

    Rather than going with the usual, ubiquitous, and often (yawn) repetitive "top 10 BI predictions" for the next year, we thought we'd try something different. After all, didn't the cult movie Highlander prove beyond the shadow of a doubt that "in the end there will be only one"? And didn't the Lord Of The Rings saga convince us that we need one prediction "to rule them all"? The proposed top BI prediction for 2014 rests on the following indisputable facts:
    • Business and IT are not aligned. Business and IT stakeholders still have a huge BI disconnect (after all these years -- what a shocker!). This is not surprising. Business users mostly care about their requirements, which are driven by their roles and responsibilities, daily tasks, internal processes, and dealings with customers (who have neither patience nor interest in enterprises' internal rules, policies, and processes). These requirements often trump IT goals and objectives to manage risk and security and be frugal and budget minded by standardizing, consolidating, and rationalizing platforms. Alas, these goals and objective often take business and IT in different directions.
    • Requirements are often lost in translation. Business and IT speak different languages. Business speaks in terms of customer satisfaction, improved top and bottom lines, whereas IT speaks in metrics (on a good day), star schemas, facts, and dimensions. Another consideration is that it's human nature to say what we think others want to hear (yes, we all want our yearly bonus) versus what we really mean. My father, a retired psychiatrist, always taught me to pay less attention to what people say and pay more attention to what people actually do -- quite handy and wise fatherly advice that often helps navigate corporate politics.
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