What you need to know to work with Data effectively!

I have met a number of developers across the globe both in person and some virtually and one thing stands out when we have a bootcamp or even a conference, everyone seems to have his own opinions on what it entails to work with data properly so as to make the most out of it .

As new technologies unveil each day one thing stands out, we all need to get to know how to handle data effectively. From insurance firms to hospitals and governments decisions informed by data seems to be the best way to go for all of us.

With the help of my collegues from imt developers, here is a small guide to enable you get to know what will be handy in working with data as your best friend:

R For statistical computing💹

Over the past few years R has stood out tall and become one of the best choice for data scientists, despite its steep curve of learning nothing beats its efficiency and numerous tools that could help you do anything with your data.

Besides a large enthusiastic community of programmers ever coming up with the best documentation and updates, it also has a rich compilation of data sets that can help you get started.

If you have worked with python before,well then things get even better. Most of us rely on either for various solutions but R has come up with a integrated development environment that helps handle your code even better across the two languages.

With numerous tools out there across blogs to YouTube tutorials you will be up and using R to handle your data better.

Probability and statistics

It is at the heart of data science and yet many shy away from it, well a sincere person will let you know from the word go that a career in a data related field and statistics are inseparable.

According to me unless you are gifted enough, you’ll probably need a real solid background knowledge in the field of mathematics know as statistics to really excel in the industry. Beginning with the principles of probability and working with different forms of data to error handling and anomaly detection in data, statistics cannot be overlooked in data science.

If you have had a chance to use tools for analyzing data such as SAS analytics or Spss you will bear me witness that for one to really use this tools effectively having the basic knowledge of statistics is fundamental.

You could be wondering , do I have to go to college to do just that? the answer is no , all you need is the will to learn then you could get a tutor or a book and read it yourself.

Knowledge in working with Databases.

We largely have two types of databases SQL and NoSQL ; SQL databases have structured queries as a primary data access languages while NoSQL do not . Since it is data that we are talking about here it is good that you know how to access data ,make the necessary changes and store it .

It recent past there has been an emerging trend in cloud computing you should also get to know that as well, Oracle has been at the fore front of providing the best cloud services you can check it out and see some of the amazing products they are offering.

When working with databases it is worthwhile having skills in data retrieval,cleaning, wrangling and user management. Databases often run using database management systems(DBMS).There are a number of resources across the internet that could help you learn about databases but I could also recommended a certificate course in Freecode camp.

Data Visualization Skills.

As a data scientists you could probably be able to understand different data formats,identify problems easily .But when working with a group of people it is good to consider that many at times we work with people from departments that might actually need help understanding what data is trying to communicate.

Data needs to be in the form that can be understood by everyone, we have amazing softwares just for that from tools like ggplot, Matplotlib, Microsoft Tableau, and many more you cab relay information easily either using charts or any diagram really.

I would be totally dishonest to conclude and say that this is all one needs to excel when working with data , there a many other skills including soft skills that one needs in order to be goood at his place of work . This and more would get going.

If you have read this far💝 you could reach out to me at and suggest anything:


Originally published at https://analyticskenya.blogspot.com on November 4, 2020.

Everything that you need to know About data and beyond.

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