Apache Tajos Big Data warehouse comes to Hadoop

The Apache Software Foundation (ASF) has just announced the relatively unknown Apache Tajo open source data warehouse software is ready for commercial use, almost two years after it first became a top-level project, and five years after its development began

Tajo is an SQL-on-Hadoop platform thats designed to help organizations extract more intelligence from their Hadoop deployments, and its first official release comes with updates that provide more connectivity to third-party databases like Oracle and PostGreSQL, plus Java programs

The software helps analyze data stored on the Hadoop Distributed File System (HDFS), as well as other data sources like Amazon S3, Openstack Swift and local file systems

Although less well-known, its somewhat similar to solutions like Apache Hive and Clouderas Impala, providing an extract, transform and load (ETL) feature set and an extensible query re-write system that lets users and external programs query data through SQL

The software could be a good fit for organizations that have outgrown their commercial data warehouses, writes Joab Jackson in Computerworld

On top of that, it could also be a useful solution for companies looking to analyze Hadoop data using more familiar commercial businesses intelligence tools, rather than the MapReduce framework.

Information is changing the way we live

Even if we arent certain what to make of big data, we all know that its, well, big

The phrase is suddenly everywhere, tripping off the tongue in domains from marketing to management to medicine

Newly massive and complex data sets, along with advanced methods of probing them, it is said, are remaking our world

Whether one believes that big data is the key to solving intractable social problems or, instead, the source of new ones say, surveillance at an unprecedentedly intimate scale we surely can agree that careful assessments of the phenomenon are in order

Enter Steve Lohr, a longtime technology reporter for the New York Times

Lohr was investigating big data before it was Big Data, and that experience lends him a somewhat different vantage point on what he calls data-ism (a word coined by his Times colleague David Brooks) from those of other devotees and detractors

His book, Data-ism: The Revolution Transforming Decision Making, Consumer Behavior, and Almost Everything Else, is a dispatch from the field, a chronicle of the present state of big data and the possible future it portends

But first: What is data-ism? Lohr describes it as a transformative way of measuring and seeing, born of improved methods of analyzing data of all kinds, from browsing histories to GPS locations to genomic information

Powerful algorithms, as well as machine-learning software and artificial intelligence technologies that can sense and communicate are at its core

More important, Lohr calls data-ism a point of view, or philosophy, about how decisions will be and perhaps should be made in the future.

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big data dominance

What does Cloudera want to be when it grows up? That was the question one analyst asked Cloudera co-founder and chief strategy officer Mike Olson at the company's analyst day this week, to which Olson responded, 'We want to be the big data company' -- not any big data company, but the big data company

By some measures, Cloudera is well on its way toward the goal, with competitors like Pivotal dropping their Hadoop ambitions -- which led Cloudera CEO Tom Reilly to effectively declare victory

But in fact, the market is still wide open

The dawn of big data Hadoop creator and Cloudera chief architect Doug Cutting made the point himself: Hadoop adoption has been doubling each year, which means half the users are newbies

As such, it's not surprising that 'lots of Hadoop use is early-stage.'

With Big Data, HR Departments Too Often Get Short Shrift

The importance of using big data to drive informed decision-making has become socialized across most organizations recently

While finance, marketing and other departments within a company receive customized data and analytics systems, human resources is still left with big data hand-me-downs

There is no one-size-fits-all blueprint for big-data infrastructure

Companies invest heavily to customize big-data and analytics tools, often on a department-by-department basis, to ensure the insights inform specific needs and strategies

Unfortunately for human resources, it is often revenue-driving departments that receive customized tools, leaving human resources to make use of infrastructure that simply doesnt fit

Human-resource departments generate and collect more data than most other areas of a company, but our attempts to claim big data for our own often get mired in technology infrastructure and analytics tools that were never intended to meet the needs of a modern HR organization.http://on.wsj.com/1AB0EWF