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Data Analytics




Introduction to Data Analytics


What is Data Analytics?

Data Analytics is the process of exploring and analyzing large data sets to help data driven decision making.


                       



Analyze Data


     


 Decision Making


Definition

Data when suitably filtered and analysed along with other related Data Sources and a suitable Analytics applied can provide valuable information to various organizations, industries, business, etc. in the form of prediction, recommendation, decision and the like.


Applications of Data Analytics

Finance & Accounting, Business analytics, Fraud , Healthcare, Information Technology, Insurance, Taxation , Internal Audit, Digital forensic, Transportation, Food, Delivery, FMCG, Planning of cities, Expenditure, Risk management, Risk detection, Security, Travelling, Managing Energy, Internet searching, Digital advertisement , etc.


Real life examples of Data Analytics

1. Coca-Cola

Coca Cola uses big data analytics to drive customer retention. In the year 2015, Coca-Cola managed to strengthen its data strategy by building a digital-led loyalty program. According to a Forbes article, Coca Cola was one of the first globally recognized brands, outside of the tech sector, to embrace Big Data. In 2015, for example, they were able to determine that Coca Cola products were mentioned online once every two seconds. Having access to this information helps them understand who their customers are, where they live, and what prompts them to discuss the brand. 


2. Netflix

Netflix is a good example of a big brand that uses big data analytics for targeted advertising. With over 100 million subscribers, the company collects huge data, which is the key to achieving the industry status.If you are a subscriber, you are familiar to how they send you suggestions of the next movie you should watch. Basically, this is done using your past search and watch data. This data is used to give them insights on what interests the subscriber most. See the screenshot below showing how Netflix gathers big data.


3. UOB Bank

UOB bank from Singapore is an example of a brand that uses big data to drive risk management. Being a financial institution, there is huge potential for incurring losses if risk management is not well thought of. UOB bank recently tested a risk management system that is based on big data. The big data risk management system enables the bank to reduce the calculation time of the value at risk. Initially, it took about 18 hours, but with the risk management system that uses big data, it only takes a few minutes. Through this initiative, the bank will possibly be able to carry out real-time risk analysis in the near future.


4. Amazon Fresh and Whole Foods

Amazon leverages big data analytics to move into a large market. The data-driven logistics gives Amazon the required expertise to enable creation and achievement of greater value. Focusing on big data analytics, Amazon whole foods is able to understand how customers buy groceries and how suppliers interact with the grocer. This data gives insights whenever there is need to implement further changes.



5. Pepsico

PepsiCo is a consumer packaged goods company that relies on huge volumes of data for an efficient supply chain management. The company is committed to ensuring they replenish the retailers’ shelves with appropriate volumes and types of products. The company’s clients provide reports that include their warehouse inventory and the POS inventory to the company, and this data is used to reconcile and forecast the production and shipment needs. This way, the company ensures retailers have the right products, in the right volumes and at the right time. Listen to this webinar where the company’s Customer Supply Chain Analyst talks about the importance of big data analytics in PepsiCo Supply chain.


Data Analytics with Excel and Power BI





Excel and Power Bi are powerful, flexible tools for every analytics activity. Both can be used to get broad data analytics and visualization capabilities. We can easily gather, shape, analyze, and explore key business data in new ways—all in less time—using both apps together.


        

Data analytics in Excel and Power BI is done by Importing the data from various sources and linking it with excel and power bi, cleaning and transform the data, manipulate and analyze the data using visuals.

  





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