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Trends and Outliers

TIBCO Spotfire's Business Intelligence Blog

Category Archives: In-Memory Analytics


Big Data Connectivity: Getting the Most Out of Your Data Assets

Big data is a double-edged sword. It offers immense potential for companies to quickly spot customer, market, and other trends that can be used to drive business and operational value.

shutterstock 68545114 150x150 Big Data Connectivity: Getting the Most Out of Your Data AssetsHowever, the steps needed to gather, store, and manage massive data sets can be daunting for IT and business leaders.

At TIBCO Spotfire, we’re continually striving to make it easier for our clients to better leverage the complete range of data assets that are available to them. Today, we’re excited to announce direct connectivity with seven repositories of big data sources.

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The Business and Productivity Benefits of In-Memory Analytics

In-memory analytics enable business users to handle significantly higher volumes of data faster than traditional analytics tools.

memory The Business and Productivity Benefits of In Memory AnalyticsThe fact is, users of in-memory analytics are able to process more than three times the volume of data at speeds more than 100 times faster than their competitors, according to a study conducted by Aberdeen Group.

That’s largely because users of in-memory analytics tools are able to access and act on data so much faster than users of traditional analytics systems since in-memory technologies can avoid latency issues.

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In-Memory Analytics: Taming the Big Data Storage Beast

These days companies are seeing greater volumes of customer, ERP, and other types of data streaming into their organizations. And this is placing an immense burden on their storage systems.

a 610x408 In Memory Analytics: Taming the Big Data Storage Beast For its part, IDC forecasts that global digital data growth is expected to undergo 50-fold growth from 2010 to 2020. Meanwhile, the volume of business data is growing at an average rate of 36% per year, according to research by Aberdeen Group.

The three key challenges often associated with big data are the “3 Vs”: volume, velocity, and variety, as Aberdeen and other industry experts note.

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