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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.
  • Make Your BI Environment More Agile With BI on Hadoop

    In the past three decades, management information systems, data integration, data warehouses (DWs), BI, and other relevant technologies and processes only scratched the surface of turning data into useful information and actionable insights:
    • Organizations leverage less than half of their structured data for insights. The latest Forrester data and analytics survey finds that organizations use on average only 40% of their structured data for strategic decision-making.
    • Unstructured data remains largely untapped. Organizations are even less mature in their use of unstructured data. They tap only about a third of their unstructured data sources (28% of semistructured and 31% of unstructured) for strategic decision-making. And these percentages don't include more recent components of a 360-degree view of the customer, such as voice of the customer (VoC), social media, and the Internet of Things.
    • BI architectures continue to become more complex. The intricacies of earlier-generation and many current business intelligence (BI) architectural stacks, which usually require the integration of dozens of components from different vendors, are just one reason it takes so long and costs so much to deliver a single version of the truth with a seamlessly integrated, centralized enterprise BI environment.
    • Existing BI architectures are not flexible enough. Most organizations take too long to get to the ultimate goal of a centralized BI environment, and by the time they think they are done, there are new data sources, new regulations, and new customer needs, which all require more changes to the BI environment.
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  • Don't Throw Hadoop At Every BI Challenge

    The explosion of data and fast-changing customer needs have led many companies to a realization: They must constantly improve their capabilities, competencies, and culture in order to turn data into business value. But how do Business Intelligence (BI) professionals know whether they must modernize their platforms or whether their main challenges are mostly about culture, people, and processes?

    "Our BI environment is only used for reporting -- we need big data for analytics."

    "Our data warehouse takes very long to build and update -- we were told we can replace it with Hadoop."

    These are just some of the conversations that Forrester clients initiate, believing they require a big data solution. But after a few probing questions, companies realize that they may need to upgrade their outdated BI platform, switch to a different database architecture, add extra nodes to their data warehouse (DW) servers, improve their data quality and data governance processes, or other commonsense solutions to their challenges, where new big data technologies may be one of the options, but not the only one, and sometimes not the best. Rather than incorrectly assuming that big data is the panacea for all issues associated with poorly architected and deployed BI environments, BI pros should follow the guidelines in the Forrester recent report to decide whether their BI environment needs a healthy dose of upgrades and process improvements or whether it requires different big data technologies. Here are some of the findings and recommendations from the full research report:

    1) Hadoop won't solve your cultural challenges

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  • Hit the road running with a new BI initiative

    Even though Business Intelligence applications have been out there for decades lots of people still struggle with "how do I get started with BI". I constantly deal with clients who mistakenly start their BI journey by selecting a BI platform or not thinking about the data architecture. I know it's a HUGE oversimplification but in a nutshell here's a simple roadmap (for a more complete roadmap please see the Roadmap document in Forrester BI Playbook) that will ensure that your BI strategy is aligned with your business strategy and you will hit the road running. The best way to start, IMHO, is from the performance management point of view:

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  • Systems Of Insight: Next Generation Business Intelligence

    Earlier Generation BI Needs A Tune Up

    Business intelligence has gone through multiple iterations in the past few decades. While BI's evolution has addressed some of the technology and process shortcomings of the earlier management information systems, BI teams still face challenges. Enterprises are transforming only 40% of their structured data and 31% of their unstructured data into information and insights. In addition, 63% of organizations still use spreadsheet-based applications for more than half of their decisions. Many earlier and current enterprise BI deployments:

    • Have hit the limits of scalability.
    • Struggle to address rapid changes in customer and regulatory requirements.
    • Fail to break through waterfall's design limitations.
    • Suffer from mismatched business and technology priorities and languages.

    Agile BI And Big Data Deliver Parts Of The Solution

    BI pros have not been resting on their laurels. Over the past few years, they have started to embrace and deploy multiple new approaches and technologies to address the limitations of earlier BI environments. Two of the most recent technology and process enhancements to BI have the potential to offer great value, but they still come up short if BI pros pursue them as two separate paths.

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  • Expand Your Big Data Capabilities With Unstructured Text Analytics

    Beware of insights! Real danger lurks behind the promise of big data to bring more data to more people faster, better, and cheaper: Insights are only as good as how people interpret the information presented to them. When looking at a stock chart, you can't even answer the simplest question -- "Is the latest stock price move good or bad for my portfolio?" -- without understanding the context: where you are in your investment journey and whether you're looking to buy or sell. While structured data can provide some context -- like checkboxes indicating your income range, investment experience, investment objectives, and risk tolerance levels -- unstructured data sources contain several orders of magnitude more context. An email exchange with a financial advisor indicating your experience with a particular investment vehicle, news articles about the market segment heavily represented in your portfolio, and social media posts about companies in which you've invested or plan to invest can all generate much broader and deeper context to better inform your decision to buy or sell.
    But defining the context by finding structures, patterns, and meaning in unstructured data is not a simple process. As a result, firms face a gap between data and insights; while they are awash in an abundance of customer and marketing data, they struggle to convert this data into the insights needed to win, serve, and retain customers. In general, Forrester has found that:
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  • An Approach To Converge The Worlds of Big Data And BI

    Webster dictionary defines a synonym as "a word having the same or nearly the same meaning" or as "a word or expression accepted as another name for something." This is so true for popular definitions of BI and big data. Forrester defines BI as:

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  • The Forrester Wave™: Enterprise Business Intelligence Platforms, Q1 2015

    The majority of large organizations have either already shifted away from using BI as just another back-office process and toward competing on BI-enabled information or are in the process of doing so. Businesses can no longer compete just on the cost, margins, or quality of their products and services in an increasingly commoditized global economy. Two kinds of companies will ultimately be more successful, prosperous, and profitable:

    • More and deeper insights will generate competitive advantage. Companies with richer, more accurate information about their customers and products than their competitors will gain substantial competitive advantage.
    • Faster access to insights will make companies more agile. Companies that have the same quality of information as their competitors but get it sooner and can turn it into action faster will outpace their peers.

    Confirming the trend, Forrester's Business Technographics® Global Data And Analytics Survey, 2014 showed that top business performers (those with 15%-plus year-over-year revenue growth) planned to invest 38% more of their technology budget in BI in 2014 than their slower-growing peers and competitors.

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  • It's Not Your Grandfather's Open Source BI Market Any Longer

    There's never been a question on the advantages of open source software. Crowdsourcing, vendor independence, ability to see and in some cases control the source code, and lower costs are just a few benefits of open source software (OSS) and business model. Linux and Apache Hadoop are prime examples of successful OSS projects. It's a different story, however, when it comes to OSS BI. For years, OSS BI vendors struggled with growth because of:

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  • Build An Agile BI Organization

    The battle of trying to apply traditional waterfall software development life-cycle (SDLC) methodology and project management to Business Intelligence (BI) has already been fought -- and largely lost. These approaches and best practices, which apply to most other enterprise applications, work well in some cases, as with very well-defined and stable BI capabilities like tax or regulatory reporting. Mission-critical, enterprise-grade BI apps can also have a reasonably long shelf life of a year or more. But these best practices do not work for the majority of BI strategies, where requirements change much faster than these traditional approaches can support; by the time a traditional BI application development team rolls out what it thought was a well-designed BI application, it's too late. As a result, BI pros need to move beyond earlier-generation BI support organizations to:

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  • Get Ready For BI Change

    To compete in today's global economy, businesses and governments need agility and the ability to adapt quickly to change. And what about internal adoption to roll out enterprise-grade Business Intelligence (BI) applications? BI change is ongoing; often, many things change concurrently. One element that too often takes a back seat is the impact of changes on the organization's people. Prosci, an independent research company focused on organizational change management (OCM), has developed benchmarks that propose five areas in which change management needs to do better. They all involve the people side of change: better engage the sponsor; begin organizational change management early in the change process; get employees engaged in change activities; secure sufficient personnel resources; and better communicate with employees. Because BI is not a single application -- and often not even a single platform -- we recommend adding a sixth area: visibility into BI usage and performance management of BI itself, aka BI on BI. Forrester recommends keeping these six areas top of mind as your organization prepares for any kind of change.

    Some strategic business events, like mergers, are high-risk initiatives involving major changes over two or more years; others, such as restructuring, must be implemented in six months. In the case of BI, some changes might need to happen within a few weeks or even days. All changes will lead to either achieving or failing to achieve a business. There are seven major categories of business and organizational change:

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