In this era of Information Technology, data is virtually everywhere whether its existence is known to someone or not.

Organizational processes generate huge amounts of data. The usability of this data depends on innovative and useful applications conceived by an organization. Data is perceived as a commodity in today's world. It has enormous value which is to be discovered within the realm of the business. Systematic approaches to capture and analyze this data help organizations gain very deep insights into the behavior of their customers and markets. Data, with proper handling, can improve the operational efficiency of an organization and has potential to radically change the business landscape.

Given the above proposition, data analytics has taken the center stage in many organizations of late. The rise of data analytics gave birth to a new field of study. Several tools and techniques, both old and new, are available to deal with data analytics or data science. Nevertheless, ample research opportunities exist in order to deal with challenges of real-time data processing, data storage and transport, predictive analytics as well as effective data visualization.

The first paper, "Reflecting Design Considerations: An End-to-End Case Study on Preparing Cricket Data Available on Net Analysis Ready", by Subhasis Ray and Kalyan Sengupta, presents an approach to trap the potential of the huge amounts of data available on various webpages on the Internet. Following a case study approach, the authors have demonstrated that the available data, which is often unusable in its inherent form, can be made highly valuable after achieving a good amount of transformation, aggregation and summarization.

Indexing techniques play a very crucial role in information retrieval domain. Most of the queries against large heterogeneous distributed databases and data warehouse systems are complex and often iterative. Right index structures are essential to improve the performance of these queries, especially the ad hock ones. The next paper, "Parsing Set of Queries to Obtain Parse Matrix for Table Index Evaluator and Recommender", by Shefali Naik, proposes an approach for table index evaluation and recommendation. According to the author, the implemented system is effective and useful in handling indexing in databases.

Sentiment analysis is a well-known text analysis approach to know the tone of a piece of text such as tweets, comments and feedbacks. The applications of sentiment analysis in business have a lot of importance, particularly in brand management. The last paper, "A Survey of Different Opinion Mining Methods", by Shubhashree Acharya and Navjyotsinh Jadeja, presents various techniques used in sentiment analysis considering different application domains. The authors also provide a pointer for further investigation on application of sentiment analysis in the field of education in order to improve the quality of educational institutions and their delivery.