Get Me A Data Scientist

Is the best way to get into the Big Data game to hire a data scientist? Not so fast. Sure, the right data scientist can get the job done. But, there are two major problems:

  1. It can be hard to find and hire that right one without getting burned
  2. Traditional data scientists often use outmoded tools and techniques that take too long to deliver results quickly.

What's the answer? Check out this dramatic, comedic video to find out.

Three Ways Mobile Apps Are Better With Contextual Sensor Data

Watch Forrester Researcher Rowan Curran explain how sensors in mobile devices and remote sensors can uniquely enable three new tiers app functionality. Also, be sure to download the full report: Use Sensors To Take Apps To The Next Level of Customer Engagement

Apps Are Blind — Use Sensors To Make Them See

Most apps are dead boring. Sensors can help add some zing. Sensors are data collectors that measure physical properties of the real-world such as location, pressure, humidity, touch, voice, and much more. You can find sensors just about anywhere these days, most obviously in mobile devices that have accelerometers, GPS, microphones, and more. There is also the Internet of Things (IoT) that refers to the proliferation of Internet connected and accessible sensors expanding into every corner of humanity. But, most applications barely use them to the fullest extent possible. Data from sensors can help make your apps predictive to impress customers, make workers more efficient, and boost your career as an application developer.

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TechnoPolitics Podcast: If You Love Your Data, Should You Set It Free?

Living in an increasingly software-mediated world, consumers are more conscious of the value of their data and concerned over its protection and stewardship. At the same time, companies realize that integration of their internal data with external partners is what will elevate personalization, contextualization, predictive apps, and customer service to the level demanded in the age of the customer.

Forrester Senior Analyst Fatemeh Khatibloo urges firms to share some of their data with other firms to drive contextually appropriate knowledge about customers. The result: A more complete view of customers that each sharing firm would not have on their own. In this episode of TechnoPolitics hosted by Rowan Curran, Fatemeh describes the rewards of adaptive intelligence and how firms can use it to gain competitive advantage.

Listen here:

 

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5 Reasons Hadoop Is Kicking Can And Taking Names

Hadoop’s momentum is unstoppable as its open source roots grow wildly into enterprises. Its refreshingly unique approach to data management is transforming how companies store, process, analyze, and share big data. Forrester believes that Hadoop will become must-have infrastructure for large enterprises. If you have lots of data, there is a sweet spot for Hadoop in your organization.  Here are five reasons firms should adopt Hadoop today:

  1. Build a data lake with the Hadoop file system (HDFS). Firms leave potentially valuable data on the cutting-room floor. A core component of Hadoop is its distributed file system, which can store huge files and many files to scale linearly across three, 10, or 1,000 commodity nodes. Firms can use Hadoop data lakes to break down data silos across the enterprise and commingle data from CRM, ERP, clickstreams, system logs, mobile GPS, and just about any other structured or unstructured data that might contain previously undiscovered insights. Why limit yourself to wading in multiple kiddie pools when you can dive for treasure chests at the bottom of the data lake?
  2. Enjoy cheap, quick processing with MapReduce. You’ve poured all of your data into the lake — now you have to process it. Hadoop MapReduce is a distributed data processing framework that brings the processing to the data in a highly parallel fashion to process and analyze data. Instead of serially reading data from files, MapReduce pushes the processing out to the individual Hadoop nodes where the data resides. The result: Large amounts of data can be processed in parallel in minutes or hours rather than in days. Now you know why Hadoop’s origins stem from monstrous data processing use cases at Google and Yahoo.
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TechnoPolitics Podcast: The Future Of Web Content Management Needs To Dazzle

Maybe it’s time to change  to your web content management (WCM) strategy. WCM systems have been around since the dawn of the Web in the 1990s, but have evolved and undergone significant enhancements in the past few years to support the dazzling digital experiences customers have come to expect. No one knows this better than Forrester Senior Analyst David Aponovich, an expert on WCM and digital experience. David is coauthor, along with Stephen Powers, of The Forrester Wave™: Web Content Management For Digital Customer Experience, Q2 2013. Vendor WCM solutions evaluated include Adobe, Acquia, Ektron, HP Autonomy, IBM, Microsoft, Oracle, OpenText, SDL, and Sitecore.

Listen to this episode of Forrester TechnoPolitics to learn, from David, how the future of WCM is evolving and what vendors are doing to create it.

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TechnoPolitics Podcast: If The Future Of Advertising Is Mobile, Then Why Is It So Lame Now?

The future of online advertising is absolutely mobile, says Forrester Principal Analyst and Research Director Melissa Parrish. The problem is that mobile advertising today is just a compact, less complex version of traditional web advertising. That’s why many advertsiers say that it’s not as effective. Something has to change to make mobile advertising more effective. That something, says Melissa, is that mobile advertising must be driven by the user’s in-the-moment context. In this episode of Forrester TechnoPolitics, Melissa analyzes the mobile mindshift and the current state of mobile advertising.

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Application Developers: Ignore Big Data At Your Own Peril

Don’t make the mistake of thinking that big data is only about analytics for business intelligence. Big data is the fuel, and predictive analytics the engine, that will power the next generation of predictive applications, as I wrote in a prior post (Predictive Apps Are The Next Big Thing In App Development). Sure, there are absolutely many exciting use cases in traditional business intelligence. But the same knowledge, insight, and predictive models gained from big data analytics can transform boring business and consumer apps with the ability to design and develop predictive apps. What are predictive apps?

Predictive apps anticipate user intent and provide the right functionality and content on the right device, at the right time, for the right person by continuously learning about them.

A Home Depot Example Of A Predictive App

Let’s say your toilet is leaking. You go to Home Depot and buy a tank repair kit. You get it home and realize that you need a special screwdriver, so you make a second trip to Home Depot. You go home and find that the screws you tried to reuse were stripped after years of decay. You make a third trip to get the screws. Finally, you can fix the toilet successfully — but it took you three trips to Home Depot. Multiple trips to Home Depot stores is pain point for many customers.

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TechnoPolitics Podcast: Next Microsoft CEO Must Divest

Steve Ballmer is quitting Microsoft. His reign as Microsoft CEO will come to an end in the next 12 months. As he put it in his resignation letter, “This is an emotional and difficult thing for me to do. I take this step in the best interests of the company I love.” Fair enough. We love your passion and stewardship of Microsoft through these changing post-PC times. However, perhaps the times they are a-changing too fast. Internet giant Google has needled Microsoft’s core business and completely eclipsed it in mobile. And Apple has become expert at winning hearts. That leaves us with the big question: How does the next Microsoft CEO need to think to prove Ballmer’s assertion that “Microsoft has all its best days ahead”?

In this episode, TechnoPolitics asks Forrester Senior Analyst TJ Keitt to offer advice to Microsoft’s next CEO to avoid looming extinction and thrive in the post-PC era. Might an IBM-style divestiture strategy might be in the cards? Listen to find out.

 

Click here to listen on iTunes.

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Predictive Apps Are The Next Big Thing In App Development

This post is based on published research. Forrester clients can read the full report here: Predictive Apps Are The Next Big Thing

Developers And Their Business Counterparts Are Caught In A Trap

They swim in game-changing new technologies that can access more than a billion hyperconnected customers, but they struggle to design and develop applications that delight customers and dazzle shareholders with annuity-like streams of revenue. The challenge isn’t application development; app developers can ingest and use new technologies as fast as they come. The challenge is that developers are stuck in a design paradigm that reduces app design to making functionality and content decisions based on a few defined customer personas or segments.

Personas Are Sorely Insufficient

How could there be anything wrong with this conventional design paradigm? Functionality? Check. Content? Check. Customer personas? Ah — herein lies the problem. These aggregate representations of your customers can prove valuable when designing apps and are supposedly the state of the art when it comes to customer experience and app design, but personas are blind to the needs of the individual user. Personas were fine in 1999 and maybe even in 2009 — but no longer, because we live in a world of 7 billion “me”s. Customers increasingly expect and deserve to a have a personal relationship with the hundreds of brands in their lives. Companies that increasingly ratchet up individual experience will succeed. Those that don’t will increasingly become strangers to their customers.

Predictive Apps: The New Design Paradigm

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