Posted by mod198 April - 24 - 2015 ADD COMMENTS

Boston, MA (PRWEB) April 22, 2015

The current process for creating and sharing analytic applications is a disjointed chain: authors create analytic programs and share only the resulting data, and none of the underlying business logic, with non-technical business analyst consumers. This broken process provides non-technical consumers with only a static, end-result report that is segregated from the source data used to develop it. Without transparency showing how results were obtained and what data were used, non-technical consumers often lack trust in the results to make key business decisions. Meanwhile, authors, in their attempts to maintain data governance, end up as bottlenecks and barriers, preventing transparency and trust.

With the introduction today of Lavastorm Analytics Engine 6.0, collaboration and transparency are finally delivered to both the authors and non-technical consumers of analytic programs. Lavastorm Analytics Engine 6.0 makes analytics a truly collaborative activity, enabling technical and non-technical users to work together on analysis, anywhere. Additionally, non-technical consumers are now given insight into an analytic program’s underlying business logic, the how and what of the results, improving transparency and trust.

In an increasingly data-driven culture accelerated by demands for Big Data technology and data storytelling, Lavastorm Analytics Engine 6.0 makes life easier for both technical and non-technical analytic users. Authors can now deliver read-only applications showing the business logic of the analytics to non-technical consumers via only a web link with no software installation required. Using that link, non-technical consumers can view data flow logic, inspect interim data, and even re-run an analytic application using dynamic parameter values to serve ad-hoc requests. Lavastorm Analytics Engine 6.0 decentralizes data access without compromising data security.

New Features of Lavastorm Analytics Engine 6.0

●    Authors can now send non-technical analytic consumers a link to an analytic application that is viewable and executable via the web on any desktop or mobile device.

●    Non-technical analytic consumers can now view the “what” and “how” of analytic applications, including data flow logic and interim data, and also execute it using dynamic parameter values.

●    A separate view-only mode is now available for analytic consumers in an HTML5 web interface that requires no installation or download.

Lavastorm Analytics Engine 6.0 Use Cases

There are a variety of scenarios where both authors and non-technical consumers would find Lavastorm Analytics Engine 6.0 to improve collaboration, process, efficiency or even results, including:

●    Quality Assurance managers can send a graph to many people in view-only mode to solicit feedback without requiring all reviewers to download software.

●    Compliance teams can file regulatory compliance reports after easily verifying that all logic and data is correct and consistent with corporate policies.

●    Run-time analysts can execute pre-built analytic applications on-demand with dynamic parameter values to serve ad-hoc requests, while maintaining overall data consistency and accuracy.

●    Analytics can be distributed to an entire organization with business logic intact, showing complete transparency into how they were created and what data was used.

●    Employees can troubleshoot analytics by viewing node properties and status through a web interface without installing or running any software.

Supporting Quotes

“In data-driven cultures, people seek to understand the process and logic behind data management and governance for analytics. Lavastorm is empowering organizations to analyze disparate data types from many different sources. Analytic application producers and consumers can now use tools such as Lavastorm Analytics Engine to gain greater visibility into their data; and identify and surface any issues associated with data quality. With this ability to collaborate across the enterprise via web-based user interfaces, Lavastorm enables organizations to take action in relation to analytical governance in a new way.”

— John Myers, Managing Research Director for Business Intelligence, Enterprise Management Associates

“Lavastorm Analytics Engine 6.0 is a new paradigm for analytics that fosters collaboration and transparency throughout the creation and sharing of analytic applications. We felt a compelling demand from not only our customers, but also the broader industry, for analytic authors to share their work. Lavastorm Analytics Engine 6.0 provides a data flow user interface that shows the what, where and how that leads to trusted analytic results.”

— Drew Rockwell, CEO, Lavastorm Analytics

Additional Resources

●    Community and Collaboration: A Big Requirement of the Big Data Landscape by Drew Rockwell

●    Collaboration Comes to Big Data and Analytics by Parag Pathak

●    Introduction to the Lavastorm Analytics Engine Video

●    Twitter – @Lavastorm_News

Lavastorm Analytics Engine 6.0 is available to Lavastorm customers beginning today.

About Lavastorm Analytics

Lavastorm is the agile data management and analytics company trusted by enterprises seeking an analytic advantage. The company’s data discovery platform empowers business professionals and analysts with the fastest, most accurate way to discover and transform insights into business improvements, while providing IT with control over data governance. The company’s solutions have identified business improvements worth billions of dollars for some of the largest corporations in the world. A global company, Lavastorm is headquartered in Boston, MA, with offices throughout EMEA and Asia-Pacific. For more information, please visit http://www.lavastorm.com.







Tags : , , , , , Big Data Challenges
Posted by jaymepobre748 September - 23 - 2014 ADD COMMENTS


Albany, New York (PRWEB) September 23, 2014

Since its inception in the year 2008, the global Hadoop market has observed growth at a tremendous pace. This market valued US$ 1.5 billion in 2012 and is estimated to grow at a CAGR of 54.7% from 2012 to 2018. By the end of 2018, this market could amass a net worth of US$ 20.9 billion. With the massive amount of data generated every day across major industries, the global Hadoop market is anticipated to observe significant growth in the future as well.


Why Hadoop
Quite naturally, the mounting scales of unstructured data generated every single day from data-intensive industries such as telecommunication, banking and finance, social media, research, healthcare, and defence led to the rising adoption of Hadoop solutions.

The major factors driving the need to adopt Hadoop are its cost-sensitive and scalable methodologies of data handling. Hadoop has taken the big data market by storm, levelling all other data management technologies that ruled the market before its inception in 2008.

Browse Full Global Hadoop Market Research Report With Complete TOC: http://www.transparencymarketresearch.com/hadoop-market.html

Some might ask, Why switch to Hadoop when RDBMS can serve the purpose? There are multiple answers but three major ones make this technology stand apart – massive data storage, faster processing, and cost effectiveness.

Hadoop can effectively run on commodity hardware and, process data in a much faster pace. Where data handling charges for one terabyte of data can take anywhere around 10 to 14 thousand US dollars with a RDBMS solution, the same requires anywhere near 4,000 US dollars with a Hadoop solution. Hourly operational cost of Hadoop is nearly 32 U.S. dollar, whereas that with RDBMS is nearly 98 U.S. dollars. The Data Warehousing Institute was able to process only 10% of its sales data in a week’s time by applying traditional data handling solutions in 2012. Now, with Hadoop-based solutions, it can handle all its sales data in just one day.

Get report sample PDF copy from here: http://www.transparencymarketresearch.com/sample/sample.php?flag=S&rep_id=719

The telecommunication industry is the major driving industry of the Hadoop market. Due to its enormous networks and the propagation of smart devices in the market, this industry has the natural tendency of producing huge volumes of data. For handling data of such massive volumes, no other technology can prove of more effect than Hadoop. The sector of government agencies is also shifting from legacy systems to Hadoop based solutions for effective data management. Due to the vast data analyzed by the retail industry, for studying consumer preferences, the retail industry also presents huge growth opportunities for the global Hadoop market.

Regional players of the global Hadoop market
From a geographic perspective, North America represents the leading regional market for Hadoop solutions, followed by Europe. North America is home to Internet technology and social media giants such as Google, Yahoo, and Facebook. Along with these Internet-based market palyers, the retail sector in this region also proposes myriad growth opportunities for the Hadoop market. Government agencies such as U.S. Department of Defense, U.S. Intelligence Agencies, and Obama Administration Big Data Initiative also use Hadoop solutions for handling and analyzing the huge amount of data generated from the entire country.

Browse the full article of this report: http://www.transparencymarketresearch.com/article/global-hadoop-market.htm

Foreword
With the data in every industry growing so rapidly, and the production of unstructured data forming nearly 90% of the data today, enterprises need to re-evaluate the methods they used for storing, managing and analyzing data. Traditional systems will remain important for handling specific low- to high-volume workloads in the future as well. But they will work in a way to compliment the use of Hadoop and optimize the data management structure in organizations. The scalability, cost-effectiveness, and streamlined nature of Hadoop will make the data more and more useful. In fact, the need for Hadoop in today’s tech-forward world is no longer a question. The only question is how to best exploit it.





Tags : , , , , , , Big Data Blogs