Data Engineers, Data Analysts, Data Scientist, Business Analysts, and Business Intelligence Role.
in this article we are going to look at the role Data Engineers, Data Analysts, Data Scientists, Business Analysts, and Business Intelligence play in helping organizations into actionable insights.
Data Engineers
Data Engineers are people who develop and maintain data architectures and make data available for business operations and analysis.
Data Engineers work within the data ecosystem to extract, integrate, and organize data from disparate sources; clean, transform, and prepare data; design, store, and manage data in data repositories.They enable data to be accessible in formats and systems that the various business applications, as well as stakeholders like Data Analysts and Data Scientists, can utilize.
A Data Engineer must have good knowledge of programming, sound knowledge of systems and technology architectures, and an in-depth understanding of relational databases and non-relational datastores.
Data Analyst
a Data Analyst translates data and numbers into plain language, so organizations can make decisions. Data Analysts inspect, and clean data for deriving insights; identify correlations, find patterns, and apply statistical methods to analyze and mine data; and visualize data to interpret and present the findings of data analysis. Analysts are the people who answer questions such as “Are the users’ search experiences generally good or bad with the search functionality on our site” or “What is the popular perception of people regarding our rebranding initiatives” or “Is there a correlation between sales of one product and another.”
Data Analysts require good knowledge of spreadsheets, writing queries, and using statistical tools to create charts and dashboards. Modern data analysts also need to have some programming skills. They need strong analytical and story-telling skills.
Data Scientists
Data Scientists analyze data for actionable insights and build Machine Learning or Deep Learning models that train on past data to create predictive models. Data Scientists are people who answer questions such as “How many new social media followers am I likely to get next month?” or “What percentage of my customers am I likely to lose to competition in the next quarter” or “Is this financial transaction unusual for this customer?”.
Data Scientists require knowledge of Mathematics, Statistics, and a fair understanding of programming languages, databases, and building data models. They also need to have domain knowledge.
Business Analyst / Business Intelligence
Business Analysts leverage the work of Data Analysts and Data Scientists to look at possible implications for their business and the actions they need to take or recommend.
BI Analysts do the same, except their focus is on the market forces and external influences that shape their business. They provide business intelligence solutions by organizing and monitoring data on different business functions and exploring that data to extract insights and actionable that improve business performance.
SUMMARIZE
- Data Engineering converts raw data into usable data.
- Data Analytics uses this data to generate insights.
- Data Scientists use Data Analytics and Data Engineering to predict the future using data from the past.
- Business Analysts and Business Intelligence Analysts use these insights and predictions to drive decisions that benefit and grow their business.
Interestingly, it’s not uncommon for data professionals to start their career in one of the data roles and transition to another role within the data ecosystem by supplementing their skills.
Thank you for reading.
References
https://www.coursera.org/learn/introduction-to-data-engineering/home/welcome
