The Predictive Modeling Process Using Machine Learning

Predictive analytics uses statistical and machine learning algorithms to find aptterns in data that might predict similar outcomes in the future. Check out this less than 3 minute, fun and fruity video to understand the six steps of predictive modeling.  For tools that use machine learning to build predictive models, Forrester clients can read The Forrester Wave: Big Data Predictive Analytics Solutions, Q2 2015 and A Machine Learning Primer For BT Professionals.

Apache Spark's Marriage To Hadoop Will Be Bigger Than Kim And Kanye

  • Apache Spark is an open source cluster computing platform designed to process big data as efficiently as possible. Sound familiar? That's what Hadoop is designed to do. However, these are distinctly different, but complementary, platforms. Hadoop is designed to process large volumes of data that lives in an Hadoop distributed file system (HDFS). Spark is also designed to process large volumes of data, but much more efficiently than MapReduce, in part, by caching data in-memory. But, to say that Spark is just an in-memory data processing platform is a gross oversimplification and a common misconception. It also has a unique development framework that simplifies the development and efficiency of data processing jobs. You'll often hear Hadoop and Spark mentioned in the same breath. That's because, although they are independent platforms in their own right, they have an evolving, symbiotic relationship. Application development and delivery professionals (AD&D) must understand the key differences and synergies between this next-generation cluster-computing power couple to make informed decisions about their big data strategy and investments. Forrester clients can read the full report explaining the difference and synergies here: Apache Spark Is Powerful And Promising
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Forrester’s Hadoop Predictions 2015

Hadoop adoption and innovation is moving forward at a fast pace, playing a critical role in today's data economy. But, how fast and far will Hadoop go heading into 2015? 
Prediction 1: Hadooponomics makes enterprise adoption mandatory. The jury is in. Hadoop has been found not guilty of being an over-hyped open source platform. Hadoop has proven real enterprise value in any number of use cases including data lakes, traditional and advanced analytics, ETL-less ETL, active-archive, and even some transactional applications. All these use cases are powered by what Forrester calls “Hadooponomics” — its ability to linearly scale both data storage and data processing.
What it means: The remaining minority of dazed and confused CIOs will make Hadoop a priority for 2015.
Predictions 2 and 3: Forrester clients can read the full text of all 8 Hadoop Predictions.
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What Qualities Do Great Enterprise Application Developers Possess?

What are you doing on October 16th and 17th? That's when Forrester's Forum for Application Development & Delivery Professionals will be held in Chicago. Join us this year for lively session, networking, and discussions about building software that powers your business. The agenda is hot including a session from me on The Unstoppable Momentum Of Hadoop and guest speaker from McDonald's on How McDonald's Plans To Leverage Its New Digital Platform To Revolutionaize Customer Experiences.

We have lots of fun at these events too. Check out this video of last year's event where we grabbed both clients and analysts and asked them an important, and to some, philosophical question: What Makes A Great Application Developer? See if you'd answer the same way.

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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