Augment significance of data science

by digital tucr
Augment significance of data science

The advances of the information technology world have evolved so much these days. The role of a data scientist is almost similar to that of a statistician and it involves machine learning, predictive learning and advanced analysis. The companies are in a keen search for data scientists to help them solve unstructured, semi-structured and structured data which collectively is known as big data.

Unstructured data contains unorganized information that does not come under a pre-defined representation. This contains potential data from social media that can help institutions in gathering information about customer needs. Structured data contains information that has already been managed by organizations in the form of spreadsheets and relational databases. Hence, multiple data forms should be managed actively in order to attain business decisions.

The demand for skilled data scientist comes from their analytical skills, mixed personal traits and experience. Their day-to-day job is to gather and analyze data. They use different types of reporting tools and analytics to detect trends, relationships and patterns in data. They are much required to break down complex data into simpler forms. A data scientist must be able to steer business decisions to creating and improving a product or services using analytical data.

Skills required by a data scientist:

Apart from being able to crush large numbers and solve complex problems, a data scientist must also have good communication skills. With better inputs, a data scientist can arrive at a solution with a better statement. Creativity along with intellectual curiosity and intuition are a few of the soft skills required by a data scientist. Interpersonal skills can also be treated as an important trait for a data scientist as they are required to present their data insights in such a way that every person at any level of the organization can understand it.

 Leadership qualities and decision making skills are two of the most important strengths of a data scientist. Experience with modeling, clustering, statistical research skills and segmentation are few among the hard skills required.

 A data scientist must have a strong foundation about mathematics that includes statistics and a background in computer programming. In programming, he must be well aware about Python, R, Perl, Scala, etc. Data science also requires a large number of tools and platforms such as Hive, Pig, Hadoop and MapReduce. A data scientist has a basic idea about data warehousing, data analyzing, machine analysis, predictive analysis and modeling.

Various tools have been introduced to simplify the techniques of data science applications. With the help of data science, companies have started to employ big data that can bring value. Due to heavy competition, customer needs and regulatory restraints, financial institutions seek new ways to gain efficiency by leveraging technology. Companies have a labor shortage in search of employing best data scientist.

Beyond having math skills, a data scientist must also possess creative abilities to create a context and meaning of the data they analyze. Standardization of data science between data scientists and business can provide data specific solutions.

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March 20, 2019
by digital tucr