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Home Business

Governance In Analytics Enables Companies To Achieve Their Goals

by Naveen Joshi
July 3, 2017 - Updated On July 24, 2017
in Business
Reading Time: 3 mins read
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Governance In Analytics Enables Companies To Achieve Their Goals
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The widespread utilization of BI, big data analytics, and performance management across organizations has given rise to the establishment of an analytic governance framework. Governance in analytics ensures that companies have effective processes, roles standards, and metrics for enabling them to achieve their goals.

Data analytics has emerged as an evolutionary step beyond traditional reporting and dashboarding. Organizations are currently focusing on implementing advanced analytic capabilities that require additional considerations, which are not addressed by existing analytics governance frameworks.

Distinct governance in analytics framework would help in addressing issues that surround the policies and processes of the analytics function. These issues can involve the integration of analytics into your organization, human capital development, and legal and regulatory concerns.

Also Read: 5 Ways Government Can Best Leverage Big Data For Nation’s Progress

Analytics requirements are constantly growing in some organizations, and its considerations need to be addressed. The following are some such considerations that give rise to the need for analytics governance.

governance in analytics

Proper data integration

As compared to traditional reporting, analytics causes a paradigm shift within organizations that requires new behaviors. Companies will be required to collaborate new processes and  managers and executives will need to trust the decision support that data analytics will provide them.

Currently, separate analytic capabilities are being built for each business function thereby, creating silos. This leads to an absence of proper standards for analytic technology procurement.

Regulations for analytics governance

The relationship between analytics and the legal and regulatory environment are often murky as some organizations are choosing to self-regulate while, others are taking advantage of the loopholes present in the existing regulations.

Human capital

Analytics and IT function are two distinct skill sets. Analytics is a business competency while, IT is a technical competency. Yet, analytics is not recognized as a distinct function and is still considered as an IT competency.

Problems to be solved with governance in analytics

  • It must provide best practices for integrating analytics into their current decision-making processes
  • It must protect financial institutions and organizations from increased liability, which is caused by enhanced and insightful analytic capabilities.
  • It must provide a proper guideline regarding the deployment, integration, and management of data mining models.

Analytics is now exploding in almost every industry. Organizations are having access to more data than ever before. Data governance will help in ensuring that you have proper structures and policies around the use of data in your organization.

Moreover, with data governance, decision makers in the finance department can effectively be visualizing billions of rows of risk data while, analysts in marketing department can open source models for identifying potential customers for a new product offer. Thus, analytics governance keeps your analytics efforts aligned, accurate, and worthwhile.

(Disclaimer: This is a guest post submitted on Techstory by the mentioned authors.  All thecontents in the article have been provided to Techstory by the authors of the article. Techstory is not responsible or liable for any content in this article.)

Image Source: diverbi.com

About The Author:

Naveen is currently the CEO at Allerin Tech Pvt Ltd. He is a seasoned professional with more than 20 years of experience, with extensive experience in customizing open source products for cost optimizations of large scale IT deployment. Naveen is a keynote speaker and thought leader in the area of IoT solutions, Machine learning and Block Chain Technology.

Specialties: Solution Design and consultancy , Data Science, Machine Learning, Deep Learning Enterprise Application Planning, Cost Optimization and Block Chain

 

Tags: Analytics GovernanceBig data AnalyticsBusiness IntelligenceData AnalysisData integrationGovernance in Analytics
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