Let us now find out the difference between data scientists and data engineers.
Data Scientists Vs Data Engineers
- Remain in constant interaction with data engineers who build the data infrastructure
- Act upon the data by making it come into use
- Utilise sophisticated machines to act upon the data or to make the data come into use
- Has a data pipeline which is basically the optimized data created by data engineer
- Do the research to identify trends and requirements of the enterprise they provide data for
- Use advanced analysis tools such as R, Hadoop and advanced statistical modelling
- Provide the data infrastructure that can be used for the particular purpose of the enterprise. For instance, for trading, making business decisions etc.
- Need to build data with high performance which is reliable for the particular purpose of the enterprise
- Use tools like SQL, MySQL which support the tools used by data scientists
- Creates a data pipeline which implies optimized data for the data scientist to be able to use it
- Help the data scientists by maintaining the data infrastructure required by them to take practical actions. For instance, feeding the data to the machine learning model for trading etc.
The main point here is that you will be needing both a data scientist and data engineer to make the data sets function appropriately. Both are critical for any enterprise involved with the use of data sets for making important decisions.
Without a data scientist, a data engineer will not be of much help since a data scientist makes the data come into actual or practical use.
Similarly, with the help of a data engineer, the data will be built without errors such as wrong entries, duplicate data etc.
Let us now take a look at the future of data engineering further.
Future of Data Engineering
As technology is rapidly changing and advancing for the better, data engineering is also transforming completely. Ever since the Internet of Things (IOT), artificial intelligence, hybrid cloud computing etc. have made their entry into domains such as financial markets, data engineers also are expected to transform and learn to utilise the same for a better functioning.
It is expected that the data engineering services market is expected to rise to USD 77.37 billion by 2023 from USD 29.50 billion in 2017 according to research.
It is expected so because there is wide adoption of big data over the past few years. And, in the future, with more technological advancements big data requirements are expected to grow and dominate the market.
This article mainly discussed the basics of data engineering. Data engineers play a crucial role in any enterprise or for trading since datasets are the most important when it comes to making decisions. Moreover, the future of data engineering is bright enough with more technological advancements and the need for big data usage.
Visit QuantInsti for additional insight on this topic: https://blog.quantinsti.com/data-engineering/.
Disclaimer: All data and information provided in this article are for informational purposes only. QuantInsti® makes no representations as to accuracy, completeness, currentness, suitability, or validity of any information in this article and will not be liable for any errors, omissions, or delays in this information or any losses, injuries, or damages arising from its display or use. All information is provided on an as-is basis.
Disclosure: Interactive Brokers
Information posted on IBKR Traders’ Insight that is provided by third-parties and not by Interactive Brokers does NOT constitute a recommendation by Interactive Brokers that you should contract for the services of that third party. Third-party participants who contribute to IBKR Traders’ Insight are independent of Interactive Brokers and Interactive Brokers does not make any representations or warranties concerning the services offered, their past or future performance, or the accuracy of the information provided by the third party. Past performance is no guarantee of future results.
This material is from QuantInsti and is being posted with permission from QuantInsti. The views expressed in this material are solely those of the author and/or QuantInsti and IBKR is not endorsing or recommending any investment or trading discussed in the material. This material is not and should not be construed as an offer to sell or the solicitation of an offer to buy any security. To the extent that this material discusses general market activity, industry or sector trends or other broad based economic or political conditions, it should not be construed as research or investment advice. To the extent that it includes references to specific securities, commodities, currencies, or other instruments, those references do not constitute a recommendation to buy, sell or hold such security. This material does not and is not intended to take into account the particular financial conditions, investment objectives or requirements of individual customers. Before acting on this material, you should consider whether it is suitable for your particular circumstances and, as necessary, seek professional advice.