Analytics

Why big data's big promises are finally within reach

Grazed from CloudTech. Author: Adam Spearing.

Let’s face it - until very recently big data has been a big letdown. Data warehouses and data analytics tools have historically proven difficult to design, build, and maintain. How much storage space will be necessary? How much data is there? What data management tools can the organisation afford and, just as important, what expertise is available in-house to build and run the data warehouse or data analytics platform?

InformationWeek recently outlined eight reasons why big data projects often fail. The article cited a survey from Gartner that found an astonishing 92% of organisations are stuck in neutral when it comes to their big data initiatives. Why? Because enterprises are spending a lot of money on big data technologies, or plan to, but don’t have the right skills or strategies in place to drive the initiatives forward...

Cloud makes enterprise-grade big data analytics widely available

Grazed from DataPipe.  Author: Chris Bateman.

The rise of big data analytics was a game-changer for just about every industry. For years, businesses have possessed tremendous amounts of raw, unstructured data that they thought was more or less unusable, as there was no way to glean valuable insight from the information in this form.

With advanced big data analytics, though, this was no longer the case. Quickly, enterprises began to leverage these big data resources, gaining unprecedented insight into their markets, as well as their own operations.  Now, increasingly, big data analytics' impact is growing, thanks to accelerating influence of cloud computing...

Predictive Process Analytics for Cloud Computing

Grazed from BackupTechnology.  Author: Editorial Staff.

Predictive process analytics assumes greater importance in cloud computing scenarios. This is especially so, as processes are executed over the Internet and they are accessed by users from multiple locations with varying levels of bandwidth and connectivity.  It is important to find answers to all of the following questions:

• How well do these processes execute?
• What are the problems being experienced by users?
• What glitches can we expect to face in the future with these same processes in place?
• What needs to be done to ensure that the processes execute as desired?...

Cloud, the great equalizer of data analytics

Grazed from ZDNet. Author: Joe McKendrick.

Is cloud computing finally opening up the doors to analytics? Everyone wants advanced data analytics, but the bar to achieving these capabilities has been high -- requiring high-level skills, as well as highly scalable data management and storage. Cloud offers a way into the world of analytics, especially for small to midsize organizations that may may never have been able to afford it.

For large enterprises, it provides ways to quickly spin up or test new applications and data sets without crowding out existing infrastructure. A recent survey by O'Reilly Media and sponsored by Teradata finds that 40 percent of respondents who identify themselves as big data practitioners currently use cloud services for analytics...

Cloud Computing: Redefining Analytics based Marketing Activities at the 2nd Annual Smart Data Summit, Dubai

Grazed from Smart Data Summit.  Author: PR Announcement.

The Middle East’s biggest Smart Data Summit, reopens its doors with an even more exciting second edition featuring stimulating presentations, roundtable sessions and case studies from an array of global experts, sharing their thoughts on enhancing customer experience across industries and sectors using smart data and analytics. This 2 day summit will be held at Sofitel Dubai The Palm Resort and Spa in Dubai, United Arab Emirates during May 25-26, 2015.

 Over 300 delegates across the GCC and worldwide are expected to attend the Smart Data Summit, which will explore the future of data management and how smart data and analytics can drive revenue growth. Focusing on using analytics to ensure superior customer experience and loyalty, the summit’s topics explore the myriad ways in which predictive big data and analytics can have a very real impact on business performance in industries such as retail, telecom and services...

More Than Half of Enterprises Have Cloud-Based Analytics Strategy

Grazed from TalkinCloud.  Author: Chris Talbot.

An end-user research study conducted by Enterprise Management Associates(EMA) uncovered data that shows more than half of enterprises consider cloud-based analytics important to their businesses.

The firm's report,"Analytics in the Cloud", found that 32 percent of respondents indicated they had adopted cloud-based strategies for analytics — and that those strategies were considered important to their business. An additional 24 percent of respondents said they had adopted cloud-based analytics strategies that were essential to their businesses...

Cloud Computing: 3 steps to buying an analytics solution

Grazed from StrategicSourcerer.  Author: Editorial Staff.

In the practice of indirect procurement, purchasing software to support various departments and operations is a concern those in charge should take quite seriously.  However, the consideration grows much more complex in regard to big data analytics. According to a 2013 report conducted by SNS Research, global investment in data analysis solutions is expected to expand at a compound annual growth rate of 17 percent between 2014 and 2020.

This technology comes in many forms, and iterations are often constructed to befit the needs of certain verticals, such as manufacturing or health care. For instance, a business specializing in qualitative data analysis tools may deliver solutions through cloud computing, a practice known as software-as-a-service.  Listed below are three steps procurement officers should follow when surveying big data analytics tools...

IBM Patents Real-Time Analytics for Cloud Data

Grazed from eWeek.  Author: Darryl K. Taft.

IBM announced it has patented an invention that enhances the use of analytics for assessing and directing data in a cloud computing environment, enabling more timely and efficient application processing and management. The IBM invention, U.S Patent #8,639,809, "Predictive Removal of Runtime Data Using Attribute Characterizing," analyzes data from a variety of sources to avoid performance lags and processing delays.

Since not all data is equal and resources for processing, storing and managing information are finite, real-time analytics can be useful in expediting this process, IBM said. "Processing data in a cloud is similar to managing checkout lines at a store—if you have one simple item to purchase, an express lane is preferable to waiting in line behind someone with a more complicated order," IBM Inventor Michael Branson, who co-invented the patented technique with John Santosuosso, said in a statement...

Cloud Computing: IBM Launches Public Beta Version of Watson Analytics

Grazed from Zacks. Author: Editorial Staff.

The recent launch comes after the private beta was made available in Sep 2014. To date, Watson Analytics has nearabout 22,000 registered members. The new service will be made available under a cloud-based freemium model through Apple's iOS, Google's Android services as well as through the web.

Watson is an artificially intelligent computer system capable of answering questions posed in natural language. Watson Analytics is a cognitive service and it automates the once time-consuming tasks such as data preparation, predictive analysis, and visual story-telling for business professionals...

Cloud Computing: Want to make data scientist money? Learn data science tools

Grazed from GigaOM. Author: Editorial Staff.

O’Reilly Media released the results of its second-annual data science salary survey on Thursday (available for free download here), and the results were not too surprising. Essentially, it shows that people who work with tools designed for big data, machine learning, statistical computing and cloud computing make more money — often between $20,000 and $30,000 more a year, based on median incomes — than people whose jobs only involve tools such as SQL and Excel.

In that regard, the survey doesn’t really tell us anything new. All the talk over the past couple years about competitive recruitment and high salaries for data scientists was true, and it was true precisely because companies want the people who know how to work with new technologies. They want this decade’s data scientists — people who can build AI systems or pipelines for streaming sensor data — not last decade’s data analysts...