13 Jul 2015
3 mins read
Big data, undoubtedly, one of the most trending buzzwords in the tech word in the 21st century. For, it is not just the large volumes of data nor the pace in which it is growing made it trending, but the strategic value that can be derived out of it for the growth of organizations made it so.
While the definition of Big Data has become clearer in terms of what it is, the adoption and implementation of Big Data is still in earlier stage. According to a recent study conducted by Gartner, only 13% of the respondents have deployed Big Data solutions in their organizations. So why is this slow adoption rate? What are the major concerns?
Here are our views on challenges/apprehensions enterprises have in implementing Big Data solutions.
Deriving value: How to decide the value for Big Data? How to estimate ROI? There are the burning questions in the minds of CIOs, IT heads. It is clear from the same study by Gartner, where 31% of respondents have mentioned that “Determining value of Big Data adoption” is their major challenge.
Where and how to start?Given that most of the organizations mayhave some IT infrastructure already existing and significant investments might have been made, defining the road-map for enterprise wide Big Data implementation and the priority of implementation with proof of concept is a key.
Risk and governance:This is another area of concern enterprises see, failing to keep track of endless amounts of data may pose potential legal and compliance risks.
Integration with existing infrastructure:Compatibility of the new big data technologies with the existing IT eco system, total cost involved in integration are other concerns enterprises have; over 14% of the respondents have mentioned it in the same Gartner report.
Implementation:It is known fact that Big Data technologies are complex in nature and often implementing the same requires new skills. Also, Big Data projects are iterative and exploratory, hence often requires different project management and life-cycle approach.
Big Leap solution, aimed at helping organizations to take competitive edge over their competitors using Big Data, addresses these challenges by enabling customers with:
Now let us look at the different solutions which customers consider as a best bet for Big Data when driven from IT. Hybrid EDW:As the data volume almost doubling every year, cost of infrastructure keeps growing at the exponential pace, also analytic and reporting queries often scan large volume of data. So, need of the hour is to have a system that shares the burden of data for easy data management and quicker analytics.
A Hybrid EDW pattern enables data storage, data processing and analytical workloads to be shared between the traditional data warehouse and the Big Data technologies thereby helping organizations in Reduced TCO, improved operational efficiency and enhanced effectiveness of Analytics
Data Hub:Fragmentation of enterprise data across transactional systems and inconsistency in data definition effectively leads to lack of agility in Analytics.
Data Hub offers enterprises an agile data management platform with robust data governance, easy integration options and a meta-data driven data processing framework thereby enabling organizations with agility in decision making, scalability to accommodate ever-growing data and availability of enterprise data for decision making across the organization
Accessible Archive:As modern businesses compete with each other on analytics, data has come to be treated as acorporate asset. Consequently, there is now an unprecedented drive to collect and preserve hugevolumes of data. The constantly evolving regulatory landscape also necessitates retention of granular historical data so that the enterprise can respond with agility to compliance and audit requirements.
Accessible Archive solution offers enterprises a highly scalable, cost-effective, reliable,secure, seamless and easy-to-access data storage solution Modern data platform: When data is getting generated across different transactional systems, the ever-growing data compounds the woes in data management and the turnaround time for data delivery to analytics is high.
Big Data solution helps enterprises to bring data to a consolidated, robust platform which not only improves performance but also delivers higher information insights at a lower cost.
Contact us to know more about our Big Data Analytics offerings
BI & Analytics
11 Jun 2020
28 May 2020
08 May 2020
24 Apr 2020
13 Apr 2020
06 Apr 2020
31 Mar 2020
26 Mar 2020
23 Jun 2017
06 Aug 2015
28 Oct 2014
17 Apr 2014
24 Mar 2014
22 Jan 2014
20 Dec 2013
01 Nov 2013
26 Sep 2013
03 Sep 2013
26 Aug 2013
29 Apr 2013
04 Mar 2013
21 Feb 2013
04 Feb 2013
03 Jan 2013
17 Feb 2012
Digital Assurance
06 Feb 2013
Digital Assurance, Enterprise Solutions
14 Feb 2013
18 Feb 2013
27 Feb 2013
Others
01 Mar 2013
Enterprise Solutions
05 Mar 2013
18 Mar 2013
Digital Assurance, Enterprise Solutions, Others
22 Mar 2013
12 Apr 2013
26 Apr 2013
13 May 2013
11 Jun 2013
17 Jun 2013
25 Jun 2013
19 Aug 2013
27 Aug 2013
10 Sep 2013
19 Sep 2013
24 Sep 2013
30 Sep 2013
01 Oct 2013
03 Oct 2013
19 Nov 2013
Enterprise Solutions, Manufacturing and Consumer
28 Nov 2013
03 Dec 2013
03 Jan 2014
27 Jan 2014
31 Jan 2014
12 Feb 2014
13 Feb 2014
20 Mar 2014
11 Jun 2014
Manufacturing and Consumer
26 Jun 2014
30 Jun 2014
10 Jul 2014
15 Jul 2014
16 Jul 2014
18 Jul 2014
26 Aug 2015
28 Sep 2015
07 Oct 2015
26 Oct 2015
Infrastructure Mgmt. Services
07 Mar 2016
22 Mar 2016
13 May 2016
23 May 2016
Application Transformation Mgmt.
11 Jul 2016
25 Aug 2016
03 Sep 2016
14 Sep 2016
15 Nov 2016
22 Nov 2016
25 Nov 2016
Business Process Services
25 Apr 2017
Banking and Financial Services
18 May 2017
30 May 2017
27 Jun 2017
18 Jul 2017
26 Oct 2017
Healthcare, Insurance
28 Nov 2017
11 Dec 2017
25 Jan 2018
21 Feb 2018
14 Mar 2018
22 Mar 2018
23 Apr 2018
15 Jun 2018
18 Jun 2018
( Mandatory field * )
The information you provide will be used in accordance with our terms ofPrivacy Policy
Please Check on "I Agree" to register for the blog.