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Big Data Analytics

In today’s world, the volume and speed at which data is produced is overwhelming. Our first instinct is to avoid it – after all, it is not easy to digest raw data into meaningful information. Investment in technology and talent are essential. But for data analytics to be truly transformative, you must have a vision for how data interacts with and impacts your business.

 

Big data helps companies to have smoother operations.

 

Companies require data analytics for a variety of reasons. It can track customers’ past purchase; recommend products to customers; or decide what to produce to maximize profit. Data analytics can also be used for business operations or intelligence. Examples include fraud detection, supply chain management, and human resources cycle.

Output

The big data lifecycle includes “Capture”, “Process” and “Output”. Companies should begin with the end: the Output, a vision for how data is used for the company’s benefit.

What type of information is needed? Will this be descriptive analytics (report on the past); predictive analytics (predict the future based on past outcomes); or prescriptive analytics (decision-making tool)? Once you know what you want from the data, you can start organizing the data source, resources and people to achieve that outcome.

The information is made available to employees on an interactive tool with dashboard and charts. The dashboard is dynamic and flexible: users can play with the dashboard to interpret data from different angles to get the right answers. In turn, the dashboard should learn from these interactions to present relevant content to users.

Capture

The Output determines Capture and Process. Depending on your output, you will need to capture the correct data sources. The large quantity of data increases the cost and the risk of incomplete data. The challenge is to build an integrated ecosystem from existing applications that makes data capture a seamless and efficient process.

Process

Companies need to invest in IT capital and talent. These are the key ingredients that drive data processing. Although there is a large upfront investment, studies show that big data analytics increase companies’ profits and demonstrate a return on investments. Companies also need to invest in talent. Human capital is crucial for problem solving and provides insight into the technology. The market is still lacking people with data analytics skills, which is why it is crucial for IT and HR departments to work together to select the suitable candidates.


Big data helps your company to run smoother and make better decisions.

 

Big data is attracting lots of attention and it is not without reason. Companies who have invested early are reaping benefits. Big data analytics can help them make informed decisions every day. This translates into better management, smooth operation, and healthier financials.

Have you joined the revolution of big data analytics?

 


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