Businesses are looking for Data Specialists who can sniff intelligent insights from the big-data goldmine they churn every day.

Data science – A broad umbrella term encompasses data analytics, data mining, machine learning together. Credit to the rapid growth of data, these three sets of professionals have become immensely important to an enterprise. While a data scientist is expected to forecast future trends based on the historical patterns, data analysts extract intelligent insights from various data sources, and machine learning experts build models on data for future prediction and strategy formulation.

Data science is a broad concept encapsulating big data it includes data cleansing, preparation, and analysis. Here is a sneak peek into the workflows and skills sets of these three data professionals-

Who is a Data Scientist?

A data scientist collates data and applies machine learning, predictive analytics, and sentiment analysis to extract meaningful and intelligent information from the collected data sets. Data scientists work on data silos and data lakes. Besides, they are also referred to being the technical professionals working on big data sets.

Those who are interested in building a strong career as a data scientist must gain knowledge of analytics, programming, and domain knowledge. Here are the industry-accepted skills to become a Data Scientist- –

• Strong knowledge of Python, SAS, R, Scala.

• Hands-on experience in coding and SQL databases.

• Familiarity to work on unstructured data collated from various sources like video and social media.

• Knowledge of Machine Learning

Who is a Data Analyst?

Data Analysts are a mix of technical and management professionals. A data analyst does the basic descriptive statistics, data visualization, and communicates data points to the management. Essential skills include a basic understanding of statistics, critical and logical thinking, and creativity to visualize data on dashboards.

A data analyst must be able to discuss data pipelines, decode the data, and communicate data story to business stakeholders. Here are the Data Analyst skills–

• Knowledge of descriptive and prescriptive statistics.

• Understanding of R, Python and Excel.

• Understanding of data structures and data warehouses.

Who is a Machine Learning Expert?

Machine learning experts use coding and algorithms for data extraction, with an aim to build data models to forecast future trends. Traditional machine learning software that comprises of statistical analysis and predictive analysis helps ML experts to identify data patterns and uncover hidden insights from data sources.

Machine learning is built on the foundation of statistics. Here are the critical skills required to be a machine learning expert-

• In-depth knowledge of coding and programming skills.

• Knowledge of statistics and probability.

• Know-how of data modelling, regression and supervised and unsupervised learning.

Developing a Multidimensional Data Science Approach

Data science brings together multiple parental disciplines, that includes data analytics, machine learning, predictive analytics, data analytics, and more. Spoken on a micro level, it includes big data retrieval, collection, and transformation for bringing a cohesive structure to big data, searching for compelling patterns, and advising the C-suite its next course of strategy formulation.

Being some of the most in-demand domains in the modern enterprise, data science, data analytics, and machine learning is here to stay. Thus, it is on you, as a data enthusiast to secure your career in these domains powering the future business gains.