I recently started learning about Microsoft power platforms and came across Power BI, an analytic tool to analyze data, visualize dashboards, and help organizations clean their data.
Research shows that data science is flourishing like never before with a wide range of insights for better decision-making and for streamlining businesses.
To get more insight into data analysis and for people wondering where and how to begin, I made the job easy. I had an amazing conversation with a Professional and he is doing well in the field.
Mr. Malachi is a good teacher and a bright Data Analyst. You can check out his Social media Page on Twitter for more.
Here are some FQAs I had with him…
Question: Can you introduce yourself?
My name is Malachi Kaselchumfa David, I am a Data/GIS Analyst. I majored in Geography as my undergraduate and transitioned into data analytics.
Question: What’s your field of expertise?
Question: Why Data Analysis?
Well first off for me, Geography involves analyzing data, be it spatial, numeric, or categorical. So that had always been my interest right from my university days.
Question: What do data analysts do?
A data analyst does a whole lot of activities ranging from data extraction, data transformation, data modeling, data visualization, data storytelling, and bringing out insights from data that has been analyzed.
Question: From our discussions, you are really into data analysis, what excites you about analyzing data?
Well, I think in all honesty, it’s the passion for me. I love what I do and that’s enough for me.
Question: How can data be used for decision-making?
Data can be used to drive decision-making in a lot of areas, modern tools use interactive dashboards to help people overcome bias and make the best insights that are inclined to their area of expertise.
Question: As a beginner, how can one start learning about data analysis?
I would say start from the basics, learn foundational tools like Microsoft Excel, and then transition into tools like Tableau or Microsoft Power BI and then a database tool like MySQL. Learn business/ industry rules, learn how to network and collaborate with others, work on projects and always believe in yourself.
Question: What are some challenges you faced when you started?
I had issues with following a path, I was overwhelmed by tools. At some point, I wanted to learn every tool and so I got burnt mentally. Then I had issues with power and internet service providers.
Question: How long do you practice in a day? And where do you get your data, and how do you clean your data?
I practice at least two hours daily. I get data from very popular data banks: Kaggle, and WHO websites. Data is ubiquitous if you ask me. For cleaning data, I follow the ETL (Extract, Transform and Load) sequence.
Question: What’s your favorite niche when it comes to data analysis and what advice would you give someone ready to choose?
I love datasets that have spatial entities, maybe it’s because of my love for Geography. For a beginner, find a niche that you love and dominate it, it could span from entertainment, sports, etc.
Question: Are there platforms that give certificate courses? Mention some
Yeah sure, Microsoft is one, here is a Link to get a Microsoft certificate, Google too, here is the Link to get google Data Analytics Cert, and Udacity, here is a Link, just to mention a few.
Question: Money is always a huge motivator, how long does one have to learn to earn
I honestly can’t answer this because we don’t have a laid down rule that says one must earn at a certain time; I believe when you put in the work with time it will definitely pay off.
Question: Are python lessons necessary when learning data analysis, what about SQL?
Python is a very wonderful tool if harnessed properly, if an analyst works in an industry that uses big data (social media data), then yes Python Programming is very necessary. SQL is also very important for an analyst too in the area of data management and storage.
Question: Which platform is preferred (Power BI, Excel, Tableau)
Personally, I will say learn all if you can, I hate to compare tools rather I feel tools complement themselves.
Question: Lastly, any take home to the guys reading
Everyone has his or her path, trust God and trust the process.
Wow! It was an interesting Moment with Mr. Malachi, and I took a lot of things with me. I hope these answers can help with some of the questions you’ve pondered on.
Here are some common uses of Data Science,
- Data science for Business management
- Data Science for Decision Making
- Data science for Product Development
- Data science for Predictive Analytics
- Data Science for Strategy Making
- Data Science for Recruitment Process
Choose which works for you and run with it. Nevertheless of the industry or organization, each of this branches have their benefits and can help in the revolutionization of businesses and may offer a competitive advantage as well.
Overall, data science is a boom for businesses in all fields. The use of technology in every domain and sector can be different but the main thing still remains the same, and that is assisting in decision making, and making things easy.
Considering the current tide towards data science and analytics, the field would soon reach the highest outfits demands which would boost the economy of industries and organizations that have and will adopt it. With such a situation rising, it would need more capable hands. If you have an interest, you can develop it starting now and pick a mentor here pay a few amount, and begin a Career in Data Analysis.
I hope this article brings more light to this topic and you consider soon.
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Thanks for your blog, nice to read. Do not stop.