Archive for February 2016

Consider the Alternatives to GSA Migration

Search Is Not at a Crossroads

Google’s recent announcement that it would discontinue support for the Google Search Appliance (GSA), in favor of a cloud-based implementation for its Google Search for Work offering seems to suggest a dilemma for enterprise architects.  But the dilemma is false and enterprise application developers don’t have to make a choice between a migration to the cloud or a future spent managing open source solutions (OSS) ...


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Big Data Profiling – Finding and Understanding Information at Scale

You’ve got Big Data? Sure, everyone’s got it. But how many organizations have indexed it all? The volume, variety, and velocity of data in a typical enterprise has by far outpaced the ability to catalog it in an orderly, easy-to-retrieve fashion.

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The Migration Away from Legacy Infrastructures to Hadoop

Data management and use was once relatively straightforward. You installed a full-stack, end-to-end solution to take care of everything from storage to reporting.

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Self-Service Data Discovery is the Key to Winning on Analytics

Can we agree that data is the new lodestar? Its accuracy is so potent that businesses that use it well have an indispensible key to success. That’s why data is now called “business’s second language” and even “the new oil.” It’s our best source of insight, confidence, and market leadership today.

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Attivio Accelerates Big Data Initiatives in Life Sciences

Today we announced an expanded relationship with PerkinElmer, a global leader focused on improving the health and safety of people and the environment, making them the exclusive OEM of Attivio licenses in the life sciences vertical.

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Risk and Compliance SCREAM HOLISTIC

The Impossible Isn’t Your Fault

The challenges you face as a risk and compliance professional reflect forces beyond your control.  You’re between an accelerating expansion in technology – which offers new avenues for misbehavior  - and a rising tide of regulatory expectations.  It’s a classic problem of supply and demand.

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Data Democratization Depends on the Middle Layer of the Data Stack

Every organization recognizes the value of agility — the ability to work with our data iteratively and flexibly, pulling data from any source as needed for insight. To achieve agility, we work and rework the data stack, adjusting and rebuilding and tweaking everything from the data lake to the visualization tools. Too often, though, we fail to achieve agility in terms of the flow of data in the organization.

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