Include Big Data in an Enterprise Wide Analytics Strategy

By Hemant Kulkarni, Deputy General Manager - Corporate IT, Kirloskar Electric Company Ltd.

Kirloskar Electric Company Limited (NSE: KECLEQ) is a Bangalore-based engineering and manufacturing company. The company caters to core sectors of the economy like power generation, transmission and distribution, industry, transportation, renewable energy etc and has a market cap of Rs 154 crores.

Cloud, Analytics, Big Data, BYOD, Mobility are the trends changing the face of IT enterprises. Cloud is being delivered by IT industry as a service providing unlimited scalability and availability. There is private cloud for internal IT, public cloud driven by third party and hybrid cloud which is a combination of both.

The challenging factor is in dealing with the growth of data which is increasing exponentially with each passing year. Problem arises since IT budgets are kept at very tight levels and there is need for data being evaluated on high performance. Challenge is to monitor growth, speed and growing complexities either through bigger systems or using efficient technologies or asking users the level of expertise they want by automating services.

In all the technologies Security Vis-a-Vis Innovation plays a vital role. The steps taken to ensure safety by analysis of their behavior or blocking the information denying access to get in and to handle the access restrictions is crucial to the role of decision makers. On TOP of that remaining in compliance is again a crucial factor bundled with security. All MNCs and big giants have their Security and Compliance policies and procedures drafted, implemented across the organization. But at certain points it becomes important to review and crosscheck the effectiveness of implementation of such policies. In this case Technology plays a vital role, providing us peace of mind and results in a good fashion for attempts in chances of failure of policies. Another challenge is to deal with the behavior of threats which are changing regularly. So before the changing in behavior of threats our technology should be ready to fight with the situation proactively.

Energy and Process industries are struggling to leverage on big data and analytics to improve profitability, mitigate risk and increase expectations for better returns on investments using these technologies. Many companies carry inflexible legacy systems, lack of enterprise-wide analytical tools and large volumes of wide variety of data (structured, semi-structured and unstructured). This creates what is known as the big data problem.

What was traditionally a monthly measurement report now becomes an everyday, hour, 15-minute event. That is the mission on which Big Data Analytics is on; to help clients manage the data and find the nuggets of actionable intelligence hidden in the data.

Big Data Analytics management is comprised of three layers – data format, data security and data transport. In data format people have a choice to use any format like – XML , XLS , EDI , CSV and in addition data has to be flexible, solution should easily scale to handle the mass volume of transactions in an efficient manner.

Finally everybody need a solution that is flexible, quick and open with less ROI and TCO.

Flexible: Adopt all possible formats for analysis.
Quick: Products need to be deployed quickly and perform competitively
Open: Ready to configure all possible future scenarios.

A fast analytical platform that can handle large amounts of transactional data and process quickly and effectively in real time is the solution foundation. It should helps companies achieve a more comprehensive—and instant—view of their assets, customers and business performance. The solution should lead to agile data visualization and the ability to leverage on sophisticated models and algorithms to predict customer behavior with Predictive Analysis.

The most immediate value analytics can provide for utility companies are—products that must handle large quantities of data every day—keep power markets functioning, detect fraud and theft and identify unbilled accounts. Energy and process companies are also starting to realize savings by using analytics to prioritize capital investments in equipment and to integrate sales and operations planning that support real-time what-if simulations and social collaboration.

In addition, by analyzing data from smart meters, utilities can gain a better understanding of customers’ consumption behavior.
Select a line of business or a region as a test bed and implement an integrated, real-time reporting and analytics solution. Using product solution, energy and process companies will quickly discover how the speed and flexibility of the platform provide immediate value to business users. Then adopt an enterprise-wide analytics strategy that includes big data. Finally companies are looking for one-stop solution that supports big data, real-time insights, agile visualization and predictive analytics.

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