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Data will fuel Industry 4.0, and empower Digital Transformation.
The world of data science has grown by leaps and bounds. The Fourth Industrial Revolution will be characterized by data. 2020 will witness the humankind generate 40x more bytes of data than there are stars in the observable universe. The data explosion will grow, to reach an estimate of 175 zettabytes in 2025 one zettabyte equals one trillion gigabytes).
To crunch this data into intelligent business insights, the most sought out professionals will be data analysts, data engineers, database administrators, data scientists, and data architects. Here is a walkthrough of the roles and what skills and technologies you will need to make data crunching a hot career in 2020-
A data analyst (DA) collects, processes, and performs statistical analyses on data. It is the job of a data analyst to analyze how data can be used to answer questions and solve problems. Data analysis has evolved over the years, credit to the development of data science and technological integration. Data analytics deploy advance excel, to gather and clean data.
Most data analysts team up with IT teams, management, and/or data scientists to mine and clean data from primary and secondary sources. The following work engages them to analyze and interpret results working on statistical tools like correlations and regression to identify data patterns for process improvement.
Technology for Data Analyst
Advance Excel, SQL, R, SAS, Python. Important skills needed are problem-solving capabilities and logical reasoning.
Data engineers are one step up the career ladder. They build and test scalable data ecosystems for data scientists to run their algorithms on the processed data systems. This data is intelligently mined, stable, and highly optimized to conduct data modeling and data visualization. It is the role of Data engineers to update existing technology systems with newer or upgraded versions to improve the outcomes of data management.
Technology for Data Engineer
Hands-on experience on R, Ruby, Java, C++, MATLAB, Hive, and NoSQL. Familiarity with popular data APIs and ETL tools is an added advantage.
Database administrators are responsible for all the databases of an enterprise and its efficient functioning. They are the professionals behind who grant or revoke the database services to the employees as per the demands of the project.
Skills for Database Administrator
Data security, data modeling, and design, database backup, and recovery.
Data scientists on a broad aspect have to work on data crunching and understand the importance of this data to meet business objectives. As senior professionals, data scientists have to work integrating the target of data intelligence and data crunching. Daily work for data scientists may include predictive analysis, and dissecting intelligence from unstructured/disorganized data to help the enterprise in meeting its objectives and formulate long term growth strategies.
Technology for Data Scientist
R, MATLAB, SQL, Python, problem-solving capabilities with a business outlook.
Data architects are the crème-de-la crème of the data profession. They brainstorm to create blueprints for data management, integrating the capabilities of data analysts, database administrators, data scientists, machine learning experts, and data statisticians. Data architects ensure that their team of data analysts, statisticians, and in particular data engineers have the updated data tools and systems to work with.
Technology for Data Architect
Data warehousing, extraction transformation, and load (ETL), data modeling expertise. Added knowledge of Hive, Pig, and Spark, and R, MATLAB, and Python.
Today's data analysts should be prepared for the change data crunching profession has to offer. If you know the industry, trends, and the latest data analytics tools, upgrading your skills into data-savvy programmers or data experts could have a significant return for your investment into data crunching.
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