Have you ever wondered the types of careers you can pursue with data science skills? Some companies use more exclusive names for these positions, say data analyst, data scientist, data engineer, data steward, etc. Generally, all these positions work within the realms of applying analysis to data.
A data analysts provides value to their company by gathering data, exploring data, and creating data visualizations to exhibit an engaging presentation. A data analyst communicates the data by making it a lot easier to be understood. This reveals patterns underneath the data which in turn helps to build a more intelligent and efficient corporate system. In different companies, the data analyst job title may vary. It may be referred as business analyst, business intelligence, database analyst, or operations analyst. Essentially, a data analyst needs to have strong knowledge of the business and also be able to process the data at hand to be able to make better business decisions.
A data scientist builds machine learning models and statistical algorithms. Data scientists need to have strong knowledge in quantitative fields, such as computer science, physics, statistics, and mathematics because they need to invent new algorithms and make predictions for any business cases based on data. Usually, data scientists use R, Python, and Java to do their job. These are the programming languages most used by data scientists. Additionally, data scientists also need to have knowledge in Hadoop, HBase, ETL, SQL, Tableau, SAS, NoSQL, and Ms.Excel. These are all frequently used data science tools.
Without big data analytics, companies are blind and deaf, wandering out onto the web like deer on a freeway.
– Geoffrey Moore, Wild Venture Partners
A data engineer creates the groundwork for a data analyst and data scientist. Data engineers are responsible for data collection, data warehouse modeling, and data transformation. Since data engineers provide the environment for other data workers, they need to have deep knowledge in Hadoop-based technologies, SQL-based technologies, NoSQL technologies, and data warehousing solutions.
A data steward is responsible for the supervision and effective use of data asset. Data stewards manage data asset and represent data needed by all stakeholders, included but not limited to any departments. Essentially, data stewards do the master data management, data cleansing, and data catalog.
Those are the job titles of people that work with data in a company. Essentially, all data workers have responsibility to turn numbers into knowledge that can be used to build a more accurate and efficient business. If you’re interested to be one of the data workers, you may kick start your data science career with Algoritma!