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Analytics & Cognitive / Business Intelligence

In its most recent report on insights-driven businesses, Forrester found that those with advanced business intelligence infrastructure are confidently growing by at least 20%. These are organizations that have been successfully enabling smarter and faster decision-making across the board through technology and data governance.

By LANSA, An Idera Inc. Company

Intelligent use of data analytics is key to optimized business processes, high customer satisfaction rates, and increased profits. With the ability to closely monitor performance and trends, companies are able to respond faster to the market – even make reliable forecasts and ultimately gain a competitive advantage.

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Although the CDO role is still evolving, a number of organizational patterns are already beginning to emerge. Companies must recognize these organizational patterns to maximize the likelihood of CDO success. 

By Sunil Soares

This article is excerpted from The Chief Data Officer Handbook for Data Governance.

Agree on the Reporting Relationship for the Chief Data Officer

There is no one single answer to where the CDO should report. This section is based on the reporting patterns that exist today. However, we anticipate that these reporting patterns will become standardized as more companies appoint CDOs. Today’s CDO may report to a number of executives as discussed below.

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I’ve been asked this question many times recently. The short answer is yes…and no. Keep reading to get a grasp on these two very important concepts and get to the long answer.

By Rafael Victória-Pereira

As explained in previous articles (parts 1, 2, and 3), having a lot of data is not, by itself, very helpful. You need tools (like the Hadoop Framework I covered in the last couple of articles) and techniques to extract value from the data. Machine Learning (ML) techniques are a good place to start. However, things get a bit fuzzy when you start reading about this topic, because it’s often mixed up with Artificial Intelligence (AI), and some articles go as far as saying that ML and AI are one and the same. This is not entirely correct. Let me start by explaining what ML is and how you can put it to good use with minimal effort.

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To effectively oversee your company's big data, your first steps are knowing what types of big data exist and then determining how to handle key areas, such as metadata, privacy, and data quality.

by Sunil Soares

This article is excerpted from Big Data Governance: An Emerging Imperative.

There are five different types of big data, and seven information governance disciplines. This chapter provides a framework so that organizations can tailor their governance programs by big data type, information governance discipline, industry, and function.

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Let's see how data is stored, using Hadoop's File System (HDFS), and processed, using the MapReduce algorithm, in the Hadoop Cluster.

By Rafael Victoria-Pereira

Last time around, I took you on a tour through Hadoop's ecosystem, or in other words, I showed you the main components of its mechanism. Now let's see what makes it tick. Note, however, that this is no easy task, and I won't explain everything in detail. I'll try to keep the explanations simple, but Hadoop is everything but simple.

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Use these guidelines to develop sound data policies for your business

By Sunil Soares

This article is excerpted from The Chief Data Officer Handbook for Data Governance.

Data governance is the formulation of policy to optimize, secure, and leverage information as an enterprise asset by aligning the objectives of multiple functions. By its very nature, data governance requires cross-departmental cooperation to deliver timely, trustworthy data for better decisions.

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This month, we’re going to start our magical journey through the wonderland of each individual Watson API. And we’ll begin with Visual Recognition.

By David Shirey

The starting point for our expedition into the world of the assorted Watson APIs will be the Visual Recognition feature that Watson provides: the ability to have Watson match up and identify an image that you have provided to it.

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It's time to continue our Big Data discussion. This article introduces the Hadoop framework, one of the most important and most commonly used tools in the Big Data world.

By Rafael Victoria-Pereira

In the previous article, I explained that the most widely accepted definition (if we can call it that) of Big Data is more data than you can manage (store, analyze, and so on) with some (usually high) intrinsic potential value. I also mentioned that these datasets are usually composed of one or more types of data-structured (think RDMS), unstructured (typically text data stored in log files), and a mix of the previous two (like JSON, for instance).

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