How data science is transforming businesses across the world

It is a well-known fact that businesses in today’s world are awash with large amounts of data. However, simply having data is not enough – businesses need to use analytical tools and cutting-edge technology in order to transform data into actionable insights. Here’s where data science comes into the picture.

In the simplest terms, data science involves studying where data comes from, what the data represents and how to convert data into a valuable resource for creating IT strategies and business strategies. Data science can help increase competitive advantage by helping a business recognize new market opportunities.

To understand why data science is so important to businesses in today’s world, let’s take a better look at what the term data science means.

What is Data Science?

Data science is an interdisciplinary field that makes uses of scientific methods in order to draw insights and extract knowledge from large amounts of data.

Data science involves a number of specialized disciplines including computer science, mathematics, and statistics and incorporates several techniques such as data mining, machine learning, visualization, and cluster analysis.

Why is Data Science important to businesses in today’s world?

As the phenomenon of big data exploded over the past few years, it has become evident that there is a tremendous amount of value in processing and analyzing data. This has given widespread rise to the growth of data science.

Here are some of the benefits that data science can offer to a business:

  • Empowers better management decisions: The insights offered by data science enables the upper management of an organization to make better strategic decisions. Data science also facilitates data-driven decision-making across the entire organization.
  • Helps define business goals based on actionable insights: Data science offers actionable insights to an organization which is based on trends. This helps direct actions based on trends, which finally help define business goals.
  • Helps identify new opportunities: Data science makes use of various scientific methods and systems in order to develop additional analytical algorithms. Due to this, data science can help a business identify new market opportunities quicker.
  • Identifying and refining target audiences: Data science enables a business to identify and target key audience groups with precision. This allows a business to tailor its products and services to meet the best customer groups.
  • Recruiting the best talent: Data science can mine large amounts of existing data to process resumes and applications from candidates. Moreover, data-driven aptitude tests and games can further help an organization make speedy recruitments.

Key Technologies that drive Data Science

As mentioned earlier, data science is an interdisciplinary field that makes use of several tools and technologies.

The process flow includes data wrangling and quality checking to transform unstructured data into a structured form, typically using SQL or NoSQL databases to created distributed or non-distributed data warehouses.

The modeling process of data science involves coming up with definitions for target variables. This includes making use of data visualization techniques in order to understand variables and their relationships in a better manner and to create additional features. Data modeling makes use of dimension reduction to create manageable feature sets and also includes other modeling techniques such as linear, non-linear and logistic regression, decision trees, random forests, and gradient boosted trees, among others.

Case Study of Data Science being used by organizations

Organizations all over the world across every industry are making good use of data science today. Let’s take a look at the example of a leading Indian microfinance institution that successfully implemented data science.

The mentioned company was facing a number of challenges. While the firm had access to large amounts of data, it needed to utilize information in order to build cross-selling models. The firm had also acquired a banking license and required the analytical framework to be set up. The company also lacked data-driven strategy development and decision making.

However, implementing data science allowed this company to address these challenges successfully. By partnering with a reliable data science firm, the company was able to analyze data from multiple channels effectively. By drawing insights and extracting knowledge from bureau data, MFI data, data rolled up to center, pin code and branch level and market data, a model, was developed. This model allowed the business to review its customer management framework completely. The model helped the organization formulate strategies for cross-selling, underwriting and retention management at the customer levels. Thanks to better customer management, this data-driven model helped the institution realize business opportunities better and increase its revenues significantly.

This is only one of many examples of organizations making good use of data science. In fact, data science is very prevalent across businesses all over the world, and if you are not making use of it, your business will suffer.

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