Leverage Data to Improve Business

Once organizations start thinking about improved outcomes, they have to revisit the customer experience as a whole. Digital transformation is a key mantra to improve the outcome. It can be broken down into improved user experience, process transformation, and personalization using data—all supported by an underlying infrastructure transformation for improved agility.

Data—and by its extension, advanced analytics—can play a critical role in this. There are two primary challenges with data—one is collecting all of the data, and the second is understanding it.

Data Collection

If you look at the data collection from a traditional sense, the points of entry include transactional systems like enterprise resource planning, customer relationship management, other transactional systems, and custom applications. These systems are good at collecting structured data. Newer data sources, which can yield valuable insights, include logs—application logs, mobile logs, and web logs; sensors; and unstructured information from external and even internal sources. Every touchpoint with the customer should be captured. It may not be possible to define the use case for the data captured up front, but, nonetheless, this is an important first step. This is one of the reasons for creating a Hadoop-based Data Lake.

The second step is to catalog the data captured—this is an important step in the journey. Many organizations do the first step well, but often struggle when it comes to cataloging the captured data.

The third step is to assess the defined data quality boundaries—this will decide whether the data is good enough to be used for analysis purposes.

The fourth step is to come up with the transformation rules that combine data from multiple sources and create a format where it is ready for consumption. Typically, in the case of customer data, this involves building a 360-degree view of the customer where all the information about the customer is collated and made available. Read more…


The article was originally published in Software Magazine in July, 2016 and is re-posted here by permission. The complete article can be accessed here.

Arvind Purushothaman

Arvind Purushothaman leads the Data & Analytics practice at Virtusa. He has over 22 years of experience in this space, and focuses on Data consulting, Data Engineering, Analytics and AI/ML.

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