Data scientists and Data engineers witnessing demand and growth

Organizations, big and small, are making significant investments in data science. New data hires are told to model anything and everything so that the organization might find a competitive edge. The problem is that few companies are investing enough in infrastructure or hiring the number of data engineers required to support modeling efforts. The purpose of Data Scientists is to extract, pre-process and analyze data. Through this, companies can make better decisions. Various companies have their own requirements and use data accordingly. The goal of Data Scientist is to make businesses grow better.

Data Science or the stream which deals with the exploration, analysis, modeling, and generation of meaningful information from data is the buzz word across industries. Organizations are increasingly recognizing that they are sitting on treasure troves of data. The immediacy to analyze this data and generate ROI is evident. The principal purpose of Data Science is to find patterns within data. It uses various statistical techniques to analyze and draw insights from the data. From data extraction, wrangling and pre-processing, a Data Scientist must scrutinize the data thoroughly. Then, he has the responsibility of making predictions from the data.

The goal of a Data Scientist is to derive conclusions from the data. Through these conclusions, he is able to assist companies in making smarter business decisions. The volume of data has really exploded, and the scale has increased, but most of the techniques and approaches are not new.

Data is the new electricity. We are living in the age of the fourth industrial revolution. This is the era of Artificial Intelligence and Big Data. There is a massive data explosion that has resulted in the culmination of new technologies and smarter products. Around 2.5 exabytes of Data is created each day. The need for data has risen tremendously in the last decade. Many companies have centered their business on data. Data has created new sectors in the IT industry.

Today, most of the data driven organizations are opening up their doors to big data and unlocking its power-increasing the value of a data scientist who knows how to tease actionable insights out of gigabytes of data. Data Engineers and Data Scientists work very closely. Data engineers build and maintain the systems that allow data scientists to access and interpret data. The role generally involves creating data models, building data pipelines and overseeing ETL (extract, transform, load). Data scientists build and train predictive models using data after it’s been cleaned. They then communicate their analysis to managers and executives.