The lure of leveraging data for competitive edge is transforming organizations to become more data driven in their operations and decisions, it has resulted in an enormous job opportunity for various data related professions. The key data roles include Data Engineering, Data Analytics and Data Science.
Data Engineering entails managing data throughout its lifecycle and includes the tasks of designing, building, and maintaining data infrastructures. These data infrastructures can include databases – relational and NoSQL, Big Data repositories and processing engines – such as Hadoop and Spark, as well as data pipelines – for transforming and moving data between these data platforms.
Data Analytics involves finding the right data in these data systems, cleaning it for the purposes of the required analysis, and mining data to create reports and visualizations.
Data Scientists take Data Analytics even further by performing deeper analysis on the data and developing predictive models to solve more complex data problems.
A Deep Dive: Skills Needed for Data Professions
In terms of skills required to perform each of these roles, while there are some unique skills for each job role, there also some common skills that all data professionals need, however the level of proficiency required may vary.
IBM and Coursera hosted a very engaging webinar with 4 IBM Subject Matter Experts and discussed each of these roles in depth.
The replay of the session can be found here:
Webinar Recording
Webinar Presentation
Some of the common questions answered can be found here
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Sonia Malik
Program Manager, IBM Training and Skills
sonia_malik@us.ibm.comTwitter : @malikmssz
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