Last Updated on by Kumar Raja

How Data Science Empowers Smart Decision Making

Over the past decade, Data Science has emerged as an eminent technology that helps business mangers’ & stake holders to take accurate decisions based on data insights. Data Science has undoubtedly become a major necessity for businesses of all types & over the years, the impact of Data Science has spread across several other sectors & this trend is expected to grow further more. 

If you are curious to know about the data analytics process in Data Science, then you can be a part of our advanced Data Science Training In Hyderabad program by expert trainers. Practically, Data Science can present solution to any challenging business problem if provided with relevant data for analysis. There are four different types of analytics techniques in Data Science that would help the stakeholders to take smart decisions. Let’s have a look at them in detail.

  • Descriptive Analytics

This is a type of analytics technique that presents us with answers to what happened. To better explain this let’s consider an example: By analyzing the overall monthly revenue and income which is generated per product group, and the total number of computers manufactured per month, manages will be in a better position to answer a series of ‘what happened’ questions & based on the analysis he get build strategies to boost the revenue.

In this analytics technique, relevant data is collected from multiple data sources & is analyzed to deliver clear insights about the past event. Descriptive Analytics when used in combination with other analytics techniques can yield better results.

  • Diagnostic Analytics

Where Descriptive Analysis gives answers to questions what happened, Diagnostic Analytics presents answers to the question why something happened. To explain this let’s consider the example: An executive can analyze the sales and gross profit data to find the reasons why his company has failed to achieve the net profit.

The applications of Diagnostic Analytics technique is also seen in the healthcare sector to find the influence of medication.

  • Predictive Analytics

This technique makes use of the findings from both descriptive and diagnostic analytics to accurately come up with predictions related to the future trends. This is the best reliable technique for forecasting. The extent of accuracy is Predictive Analytics is largely dependent on the quality of data used.

  • Prescriptive Analytics

This type of analytics technique deals with what is the best possible action to take for any given situation. This technique makes use of advanced tools, modeling techniques and as well as ML algorithms that need to be trained with the existing business data & as well as external information for better accuracy.

Build real-world expertise in relation to working on these analytics techniques by joining for our Kelly Technologies advanced Data Science training program.

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