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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Developers: Will AI Run You Out Of Your Job?

Diego Lo Giudice

Much has been written about how artificial intelligence (AI) will put white-collar workers out of a job eventually. Will robots soon be able to do what programmers do best — i.e., write software programs? Actually, if you are or were a developer, you’ve probably already written or used software programs that can generate other software programs. That’s called code generation; in the past, it was done through “next” generation programming languages (such as a second-, third-, fourth-, or even fifth-generation languages), today are called low code IDEs. But also Java, C and C++ geeks have been turning high level graphical models like UML or BPML into code. But that’s not what I am talking about: I am talking about a robot (or bot) or AI software system that, if given a business requirement in natural language, can write the code to implement it — or even come up with its own idea and write a program for it.

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Another Agency Gets Gobbled Up: Accenture Announces The Acquisition Of Karmarama

Anjali Yakkundi

Over the past few years, we’ve seen a flurry of consultancies acquiring agencies. Acquity, BGT Partners, Lunar, and Cynergy  are just some of the agencies that have been scooped up. The agencies and consultancy convergence has radically altered the conversation for marketers looking to purchase marketing services. They now have a new category of provider to consider and new capabilities to assess across the board. And marketers are paying attention: 73% of marketers told us in a recent survey that they were somewhat open, open, or very open to using consultancies for digital marketing work.

 
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Take a Pragmatic Approach To Personalization

Anjali Yakkundi

Co-authored by Allison Cazalet 

Has the topic of personalization come up within your organization recently? Chances are that personalization not only comes up, it’s also a foremost priority: 68% of the firms we surveyed in our Q1 2016 Digital Experience Delivery Online Survey said personalization was one of the most important initiatives for their business today. Why? Because personalization is one of the best ways to contextually engage with customers across a variety of touch points. But many organizations we speak with today struggle to get initiatives off the ground and struggle to prove the business value of personalization.

To help organizations get started on their personalization program, my colleague Ted Schadler and I researched how best-in-class organizations today have operationalized personalization. The most successful firms we spoke with created a four-pronged personalization program that Forrester calls POST:

People – Before doing anything else, successful firms ask and answer this question: Which customers am I trying to reach and serve? In order to implement a successful personalization program, you will need to do the same by researching your customers in their context so that you know which ones to prioritize.  

Objectives – The next step to a successful personalization program is to make sure you and your personalization team have an in depth understanding of what you are trying to accomplish. You must keep this simple. Determine what business outcome you are optimizing, the experiences you will personalize, and what data you need to make it all happen.

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Is Data Visualization A Separate Market Or Just A Feature Of Business Intelligence Platforms?

Boris Evelson

Lots of my clients are confused. They start a Forrester inquiry with a question about data visualization capabilities, but when I lead them into discussion about business intelligence (BI) platforms, they say "but we already have a BI platform. All we really want is an ability to create and share data visualizations". Is there a separate market for that? If there is, I am not aware of one. Here's my take on it:

  • If what you are looking for includes requirements for data visualization administration, security, data management, version control, collaboration, etc, you really need a BI platform with data visualization capabilities.
    • The last time Forrester looked at Data Visualization as a separate capability was in 2012 and even then, as you will see from the URL, we ended up evaluated BI platforms.
    • In our last (and going forward) Wave on the topic we grouped data visualization and self service BI capabilities together as we see them inseparable.
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AI Is The Sincerest Form of Flattery ... And Fear

Mike Gualtieri

Pure AI is true intelligence that can mimic or exceed the intelligence of human beings. It is still a long way off, if it can even ever be achieved. But what if AI became pure — could perceive, think, act, and even replicate as we do? Look to humanity for the answer. Humanity has been both beautiful and brutal:

  • The beauty of ingenuity, survival, exploration, art, and kindness.
  • The brutality of crime, war, and pettiness.
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Micro Explanations For Nine Essential AI Technologies

Mike Gualtieri

Artificial Intelligence is rampant in the movie Ex MachinaArtificial Intelligence (AI) is not one big, specific technology. Rather, it is comprised of one or more building block technologies. So, to understand AI, you have to understand each of these nine building block technologies. Now, you could argue that there are more technologies than the ones listed here, but any additional technology can fit under one of these building blocks. This is a follow-on to my post Artificial Intelligence: Fact, Fiction, How Enterprises Can Crush It

Here are the nine pragmatic AI technology building blocks that enterprises can leverage now:

■        Knowledge engineering. Knowledge engineering is a process to understand and then represent human knowledge in data structures, semantic models, and heuristics (rules). AD&D pros can embed this engineered knowledge in applications to solve complex problems that are generally associated with human expertise. For example, large insurers have used knowledge engineering to represent and embed the expertise of claims adjusters to automate the adjudication process. IBM Watson Health uses engineered knowledge in combination with a corpus of information that includes over 290 medical journals, textbooks, and drug databases to help oncologists choose the best treatment for their patients.

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Meet The Digital Architects Of Your Technology Strategy

Ted Schadler
When Jeffrey Hammond, Mark Grannan, Adrian Chapman, and I dove into our most recent developer survey, we unearthed a fascinating group of developers we call "digital architects." This group aspires to set architectural direction, deploys open source software across four or more technology areas, and uses three or more types of cloud services (see the figure). 
 
  • One in 11 enterprise developers. Only 9% of the developers in North America and Europe are digital architects. This small segment is an elite and attractive group, with particular enthusiasm for technology and, as we'll see, for digital innovation and customer engagement.
  • More likely to work at fast-growing companies. More than half of digital architects — 53% — work at companies growing at double-digit rates. You'll find them in all three sectors of the software business: enterprises, software vendors, and service providers.
  • Younger than the rest. Almost three-quarters of digital architects are younger than 45, and 30% are younger than 35. That means these technologists came of age during the internet and smartphone era. They think digital because they know nothing else.
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Artificial Intelligence: Fact, Fiction. How Enterprises Can Crush It

Mike Gualtieri

Forrester surveyed business and technology professionals and found that 58% of them are researching AI, but only 12% are using AI systems. This gap reflects growing interest in AI, but little actual use at this time. We expect enterprise interest in, and use of, AI to increase as software vendors roll out AI platforms and build AI capabilities into applications. Enterprises that plan to invest in AI expect to improve customer experiences, improve products and services, and disrupt their industry with new business models.

But the burning question is: how can your enterprise use AI today to crush it? To answer this question we first must bring clarity to the nebulous definition of AI.Let’s break it down further:

■        “Artificial” is the opposite of organic. Artificial simply means person-made versus occurring naturally in the universe. Computer scientists, engineers, and developers research, design, and create a combination of software, computers, and machine to manifest AI technology.

■        “Intelligence” is in the eye of the beholder.  Philosophers will have job security for a very long time trying to define intelligence precisely. That’s because, intelligence is much tougher to define because we humans routinely assign intelligence to all matter of things including well-trained dachshunds, self-driving cars, and “intelligent” assistants such as Amazon Echo. Intelligence is relative. For AI purists, intelligence is more akin to human abilities. It means the ability to perceive its environment, take actions that satisfy a set of goals, and learn from both successes and failures. Intelligence among humans varies greatly and so too does it vary among AI systems.

Temper Your Expectations, But Don’t Give Up On AI

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In 2017, Digital Transformation Budgets Will Top The Billion-Dollar Bar

Ted Schadler
Check out our Predictions 2017: In Digital Transformation, The Hard Work Of Operational Excellence Begins piece that went live this morning. It has more predictions and more detail from from my coauthors Nigel Fenwick and Martin Gill.
 
You've been creating digital customer experiences for years now. You've built a successful app. You’ve assembled a martech/adtech stack. You may even have started swinging at omnichannel delivery or harnessed AI or piloted a connected product. So it’s time to declare victory on digital transformation, right? [In our 2016 services survey, a shockingly high 19% have . . .]
 
Not so fast. Digital customer experiences are only the shining faces of a digital business. Those pretty faces quickly lose their luster unless you’ve also transformed your business operations to make them better every single day -- and introduce new digital faces all the time. We call this capability "digital operational excellence." It’s the 80 in the 80/20 rule of digital transformation. Here are three predictions for 2017 to prod the digital business conversation:
 
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