Business Intelligence Skills

Boris Evelson

So you have gone through the Discover and Plan of your Business Intelligence (BI) strategy and are ready to staff your BI support organization. What skills, experience, expertise and qualifications should you be looking for?

  • Since the term BI is often used to also include data management processes and technologies, let's assume that in your case you are only looking for expertise required to build reports and dashboards and it does not include
    • Data integration (ETL, etc) expertise
    • Data governance (master data management, data quality, etc) expertise
    • Data modelling (relational and multidimensional) expertise
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Insight Platforms Have Arrived

Brian  Hopkins

Are you lost in a confusing soup of vendor-speak about what their data analytics stack actually offers? Big data, data platforms, advanced analytics, data lakes, real-time everything, streaming, the IoT, customer analytics, digital intelligence, real-time interaction, customer decision hubs, new-stuff-as-a-service, the list goes on.

Recognize the convergence happening as vendors evolve their technologies from doing just one thing like predictive analytics or search to many things together. For example, data integration, data warehouse, and BI tools are typically sold separately, but breakout vendor Looker combines data integration, model governance, basic BI, and a runtime for data applications all in one software layer that sits on your data lake. As another example, consider predictive analytics vendor Alpine Data Labs or SAS Viya from SAS. These vendors have built out a lot of data management and insight delivery tooling into their platforms because without it users struggle to maximize value. Another trend is big data search vendors like Maana that now also include hooks for predictive model execution as well as more data management functions. Lastly, systems integrators are packaging their IP and offering it as a data management and analytics integrated product — for example, Saama’s Fluid Analytics Engine or Infosys’ Information Platform.

In fact, the list of innovative vendors blending data management, analytics, and insight execution technology is growing by leaps and bounds. To address this trend, I just published a report, Insight Platforms Accelerate Digital Transformation, in which I created a broad definition that labels this trend:

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Let’s Put Enterprise Marketing Technology Into Context

Rusty Warner

Context – noun –  con·text – \ˈkän-ˌtekst\

What is context? According to Merriam-Webster, context is “the situation in which something happens or the group of conditions that exist where and when something happens.” We’ve been using it since late Middle English speakers adapted the Latin contextus, from con (together) and texere (to weave). For marketers, context means understanding attitudes, behaviors, and preferences to address the requirements of individual customers in their moments of need.

It is critical for marketers to embrace customer context. Why? Winning in the age of the customer depends on the interactions that people have with your brand, and compelling customer experiences materialize only when your firm understands its customers and anticipates their needs.  The context of all those interactions determines whether customers will engage and, more importantly, transact with your brand again. Marketing’s job is to harness the power of customer context to create a repeatable cycle of interactions, drive deeper engagement, and learn more about the customer in the process.

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Four Rules To Build Successful Business Intelligence Business Cases

Boris Evelson

Rule #1. Don't just jump into creating a hefty enterprise wide Business Intelligence (BI)

Business intelligence and its next iteration, systems of insight (SOI), have moved to the top of BI pros' agendas for enterprise software adoption. Investment in BI tools and applications can have a number of drivers, both external (such as regulatory requirements or technology obsolescence) and internal (such as the desire to improve processes or speed up decision-making). However, putting together a BI business case is not always a straightforward process. Before embarking on a BI business case endeavor, consider that:

  • You may not actually need a business case. Determining whether a BI business case is necessary includes three main considerations. Is it an investment that the organization must make to stay in business, should consider because other investments are changing the organization's IT landscape, or wants to make because of expected business benefits?
  • A business sponsor does not obviate the need for a business case. It may be tempting to conclude that you can skip making a business case for BI whenever there is a strong push for investment from the business side, in particular when budget holders are prepared to commit money. Resist this impulse whenever possible: The resulting project will likely suffer from a lack of focus, and recriminations are likely to follow sooner or later.
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Welcome to my customer analytics blog!

Brandon Purcell

Greetings!  My name is Brandon Purcell and I am the new Senior Analyst serving Customer Insights professionals at Forrester.  I will cover customer analytics which uses advanced analytics to analyze customer data to optimize customer-focused programs and initiatives to drive acquisition, retention, cross-sell/upsell, loyalty, personalization, and contextual marketing. I am a recovering customer analytics practitioner and come to Forrester from a boutique consulting firm where I led a team of data scientists that helped our clients solve their urgent business challenges by harnessing the latent value in their customer data.  A few highlights from my former life:

  • I helped develop a best in class Voice of the Customer program at one of the country’s largest banks
  • I created and led many trainings in business applications of predictive analytics
  • I built a patented algorithm that uses geospatial data to predict a person’s future location
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