Posts by David Loshin:

An Introduction to NoSQL Data Management for Big Data

by   |   September 4, 2013   |   1 Comment

NoSQL data systems provide a flexible model that enables automatic distribution of data and elasticity with respect to the use of computing, storage, and network bandwidth in ways that don’t force specific binding of data to be persistently stored in particular physical locations. This article introduces the concepts behind the growing popularity of NoSQL in the development of analytics applications.
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How Pig, Hive and Zookeeper Build Apps on Hadoop and MapReduce

by   |   July 23, 2013   |   2 Comments

It may be straightforward to download the core components of Hadoop and MapReduce, but designing, developing, and deploying analytic applications still requires some skill and expertise. This article examines the prototypical big data platform using Hadoop, and how Pig, Hive, HBase, Zookeeper and Mahout address these pieces of the puzzle.
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Understanding the Big Data Stack: Hadoop’s Distributed File System

by   |   July 15, 2013   |   Leave a comment

Hadoop is a collection of open source projects that are combined to enable a software-based big data appliance. This introductory article begins with a core aspect of Hadoop’s utilities, upon which the next layer in the stack is propped—the Hadoop Distributed File System.
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An Introduction to Big Data Application Development and MapReduce

by   |   June 7, 2013   |   Leave a comment

For any target big data platform, you must have an application development framework that supports a system development lifecycle and provides a means for loading and executing the developed application. This article discusses the principles involved and how programmers use the MapReduce and ECL frameworks to analyze big datasets. Read More…

Considerations for Storage, Appliances and NoSQL Systems for Big Data Analytics Management

by   |   April 1, 2013   |   1 Comment

Big data management and analytics applications rely on an ecosystem of components that can be combined in a variety of ways to address application requirements. This article examines three aspects of this ecosystem and associated technologies: storage, appliances, and data management. Read More…

Data Governance for Big Data Analytics: Considerations for Data Policies and Processes

by   |   February 12, 2013   |   Leave a comment

With emerging big data use cases, datasets created for one purpose can be used for an entirely different purpose—a dynamic that challenges traditional approaches to data governance. This article, part of a series on implementing big data analytics, explores ways to manage this conflict and build new governance policies. Read More…

Developing a Strategy for Integrating Big Data Analytics into the Enterprise

by   |   January 7, 2013   |   Leave a comment

As with any innovative technology that promises business value, there is a rush to embrace big data analytics as a key source of business value. This article, the fourth in a series, explains how to consider the challenges and issues involved in bringing big data analytics into production. Read More…

Achieving Organizational Alignment for Big Data Analytics

by   |   November 20, 2012   |   Leave a comment

Numerous aspects of big data analytics hold appeal, and while individuals within an organization can “test drive” them, these new technologies need to win adoption in a broader enterprise setting. Managers need to answer: What is the process for piloting technologies to determine their feasibility and business value? And: What must happen to bring big data analytics into organization’s system development lifecycle? Read More…

Hurdling image by Rodrigo Moraes via Wikipedia

Business Problems Suited to Big Data Analytics

by   |   October 18, 2012   |   Leave a comment

Enterprises need clear processes for determining the value proposition of a big data analytics project. In this article, David Loshin examines the applications that make sense for these projects and the criteria that enterprises should use to weigh the costs and benefits of such a strategic investment. Read More…

Market and Business Drivers for Big Data Analytics

by   |   September 16, 2012   |   4 Comments

To best understand what “big data” can mean to your organization, start by understanding the conditions that has led to its growing acceptance. In this article, the first in a series, David Loshin explains the economic drivers that make new analytics applications worth evaluating given today’s exploding data volumes, and the technology innovations that make such systems more accessible to more companies. Read More…