Another Word For It Patrick Durusau on Topic Maps and Semantic Diversity

February 20, 2013

LucidWorks™ Teams with MapR™… [Not 26% but 5-6% + not from Big Data]

Filed under: LucidWorks,MapR — Patrick Durusau @ 9:24 pm

LucidWorks™ Teams with MapR™ Technologies to Offer Best-in-Class Big Data Analytics Solution

Performance Day just keeps on going!

From the press release:

REDWOOD CITY, Calif. – February 20, 2013 – Big Data provides a very real opportunity for organizations to drive business decisions by utilizing new information that has yet to be tapped. However, it is increasingly apparent that organizations are struggling to make effective use of this new multi-structured content for data-driven decision-making. According to a report from the Economist Intelligence Unit, the challenge is not so much the volume, but instead it is the pressing need to analyze and act on Big Data in real-time.

Existing business intelligence (BI) tools have simply not been designed to provide spontaneous search on multi-structured data in motion. Responding directly to this need, LucidWorks, the company transforming the way people access information, and MapR Technologies, the Hadoop technology leader, today announced the integration between LucidWorks Search™ and MapR. Available now, the combined solution allows organizations to easily search their MapR Distributed File System (DFS) in a natural way to discover actionable insights from information maintained in Hadoop.

“Organizations that wait to address big data until this evolution is well under way will lose out competitively in their vertical markets, compared to organizations that have aggressively pursued big data flexibility. Aggressive organizations will demonstrate faster, more accurate analysis and decisions relating to their tactical operations and strategic planning.”

  • Source: Big Data Drives Rapid Changes in Infrastructure and $232 Billion in IT Spending Through 2016, Gartner Group

Integration Solution Highlights

  • Combines the best of Big Data with Search with an integrated and fully distributed solution
  • Supports a pre-defined MapR target data source within LucidWorks Search
  • Enables users to create and configure the MapR data source directly from the LucidWorks Search administration console
  • Leverages enterprise security features offered by both MapR and LucidWorks Search

The Economist Intelligence Unit study found that global companies experienced a 26 percent improvement in performance over the last three years when big data analytics were applied to the decision-making process. And now, those data-savvy executives are forecasting a 41 percent improvement over the next three years. The integration between LucidWorks Search and MapR makes it easier to put Big Data analytics in motion.

I’m really excited about this match up but you know I can’t simply let claims like “…global companies experienced a 26 percent improvement in performance….” slide by. 😉

If you go read the report,
The Deciding Factor: Big Data & Decision Making
, you will find at page six (6):

On average, survey participants say that big data has improved their organisations’ performance in the past three years by 26%, and they are optimistic that it will improve performance by an average of 41% in the next three years. While “performance” in this instance is not rigorously specified, it is a useful gauge of mood.

The measured difference in performance, from:

firms that emphasise decision-making based on data and analytics performed 5-6% better—as measured by output and performance—than those that rely on intuition and experience for decision-making.

So, not 26% but 5-6% measured and the 5-6% is for decision-making on data and analytics, not big data.

You don’t find code written at either LucidWorks or MapR that is “close enough.” Both have well deserved reputations for clean code and hard work.

Why should communications fall short of that mark?

No Comments

No comments yet.

RSS feed for comments on this post.

Sorry, the comment form is closed at this time.

Powered by WordPress