Technical Skills Required to become Data Scientist

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27 Sept 2022
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Over the years, companies have come to realize the importance of historical data in their businesses or organization. Companies are starting to enjoy the availability of insight and predictive models done by data analysts and data scientists. Thus making data science the most desired, most sorted job, and highly paid job presently.

The path to becoming a successful data scientist is not easy as it may sound. Skills sets required  to master your career in this field, you’re required to be an expert handling this set of tools and languages along with statistical computations.


Tools For Basic Programming

Data scientists require knowledge of programming languages to be able to manipulate the data and apply sets of algorithms to data and generate insight. Major languages that are used by data scientists:
Python
R Programming
SQL- (structured query language) is a programming language that can help you to carry out analytical functions and transform database structures.

Statistics

Having a strong understanding of statistics and mathematics gives you a base to your career and also ensure that you’re learning them thoroughly so that you can implement them in any real-life scenarios. You could earn a Bachelor’s degree, Master's degree, or Ph.D. in Computer science, Social sciences, and Statistics. The most common fields of study are Mathematics and Statistics, followed by Computer Science and Engineering. 


Tools for Data Visualization

Being a data scientist would require you to work on data visualization to display the pictorial forms of charts and graphs that can be easy to understand. Tools being used are:
Tableau
Power BI
Matplottlib
Qlikview
D3.js


Big Data

As a Data Scientist, you will have to deal with large amounts of data. Because data is being generated every day. Big data querying is primarily used to capture, store, extract, process and analyze useful information from different data sets.



Hadoop Platform 

An open-source platform used to store and process large sets of data that can extend from gigabytes to petabytes. Hadoop platform is used when the volume of data you have exceeds the memory of your system or you need to send data to different servers. Hadoop can also be used for data exploration, data filtration, data sampling, and summarization.














References 

[1] BULB, 'Write to Earn. Read to Earn' (online, 2022) <https://www.bulbapp.io/>

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7 Comments

B
M.L.C
M.L.C
now
Intelligently illustrated
andrewsaul
andrewsaul
now
So I respectfully disagree. The only hard skill you NEED is SQL and an understanding of relational databases. Everything else is up to interpretation. At one stage Hadoop was hot, then it was log stores/data lakes, then streaming data & immutable logs (think Kafka) and now... I suppose ML is back, dressed as AI to have another crack? To be a data scientist I think you you need to understand complex data problems. And for that you really need a whole lot of theory and data history. You need to understand the underlying concepts that made Hadoop attractive and the different underlying concepts that made Kafka attractive. I'm old enough to remember at one stage every man and his data dog wanting to turn all data into value pairs and drop it in unstructured stores. Schema on demand was so hot, so hot it melted servers with the massive increases in processing need to replace the functionality of most star schema relational models.
Draxpart
Draxpart
now
Well written articles with indepth knowledge and lots of useful information in it. To become a data analyst expert, one needs to have a strong foundation in statistics, programming languages such as SQL, Python or R, and data visualization tools. Additionally, expertise in data cleaning, analysis, and interpretation, along with domain-specific knowledge, communication skills, and a curious mindset are essential for success in this field. As of now, I am proficient in Python and have experience in conducting data exploratory analysis. Additionally, I have some knowledge in implementing algorithms for data analysis and interpretation
Diana jade
Diana jade
now
You gave me hope
M.L.C
M.L.C
now
Till morning
Leenah
Leenah
now
I want to be a data analyst