Data Analytics: Dawn of success

Data Analytics

Our quest for data analytics started by wondering how can a software detect person’s age and health conditions even after 10-15 years!!

Gradually we started discovering new facts and noticeable factors related to it and was actually amazed to see what wonders data can do if brought under process by certain methodologies. For many of the world’s renowned organizations, these data sets are helpful to draw deep inferences and make long term as well as short term strategic plan and take decisions accordingly.

It has been observed that Data Analytics is a set of procedure for examining various data points to draw various conclusions and observations on a set of information. These observations are then helpful to draw certain conclusions with the aid of specialized systems and software like SQL, R-Language, SAS, Excel, SPSS, Minitab, Hadoop and much more by various scientific models, theories, and hypotheses.

Interestingly, all these tools, techniques and technologies are being used widely in this century in almost all the commercial organizations and industries to make informed decisions more accurately for business decisions.

It is amply clear through various research and studies that various efforts and initiatives for data analytics have always resulted in a potential increase in revenues, improvement in operational efficiency, optimization in marketing campaigns, track on customer service efforts, emerging market trends and gaining a competitive edge over competitors. In short, a one-stop for knowing and strategizing all the necessary factors that ultimately contribute in boosting business performance in real time.

Of course, we get different outputs through differing ways and various means, and different approach by undertaking different methodologies. While Exploratory data analysis (EDA) is to unearth various trends, patterns, and relationships between data points, Data Mining is used for similar purposes but on larger data set. Confirmatory Data Analysis (CDA) is popular for its ease that enables application of various statistical techniques for determination of hypothesis. Text Mining has extended its reach on analyzing e-mails, documents, and other text-based content as well. For beginners in this industry Quantitative Analysis is to quantify variables to compare and measure them statistically whereas Qualitative Analysis serves to interpret for understanding non-numeric data like text, images, video and audio with common themes and various view points. When Descriptive Analytics has helped organizations to picturize the true events of present and past situations, Predictive and Prescriptive Analytics has unearthed these capabilities through its ability to predict future of these events along with probabilities of events like Seismic detection, Cardiac Attack Detector, Google App and Age Detector. Machine Learning and Artificial Intelligence have changed the ongoings of Military and National Security Services by making use of automated algorithms. These days scientists have gone ahead through Big Data Analytics to perform data mining, predictive and prescriptive analysis on semi-structured and unstructured data as well.

A well-organized approach is undertaken in various organizations to obtain the desired result:

Process

We are staying in a century of technological advancements and achievements. Data analytics is the food for the emerging new phase in technology. Many marketing, advertising, E-commerce companies undertake clickstream analysis to identify website visitors, page viewing trends, and patterns, potential buyers for various products and services, etc. Health Industry examines patient data for effectiveness of treatment of cancer, diabetes and other diseases. Financial Organizations, Credit cards, and Banks analyse spending and withdrawal trends and patterns based on geographies and other parameters to detect fraud and identity theft. Marketing Companies through CRM Analytics segment their customers, marketing campaigns and various parameters for organizational growth. Mobile companies forecast churning customers to prevent business from rivals, increase service levels and boost customer relationships.

To sum up it is well understood that Data Analytics allows you to make more informed decisions that help to strategize your operational efficiencies, working effectiveness, improve quality and develop cost competitive new technologies and products to measure value, time and effort.

PMaps Assessment helps corporates in achieving these dreams and to have a competitive position in the market. PMaps has expertise on HR Analytics, Predictive Analytics, and Descriptive Analytics. Our research-driven, consulting approach enables our clients with customized service and customized products designs through our deep analysis on cultural understanding.

Nikita Bhatkar

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