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Imagine yourself working as data analyst in a company. You get different king of ad-hoc analysis request every day. To resolve those request you are using several programming tools (Dataframe, Distribution etc.), querying to databases. At the end of the projects you also git your code so that you can use it further when it needs or you can share you code to other colleagues when they need or may be your project should be in QA (git) before it sent to the clients.

  • But the project has a start and where to start?: You might want to have a…

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My resolution of new year was learning modern languages. I start learning Go and Julia on January, 1 2020. First I was afraid that is that any good, learning two language at the same time? But as I go further, I notice there is concept common in both languages and it is possible to learn these 2 language together. Actually they can be a good combo for modern data science stack.

Why learning go and Julia both? Actually my plan was to try this 2 languages and choose the one I like most. My primary language is Python and I…

I was enrolled in the Full-Stack nano degree program around end of November 2019. More precisely Sat, Nov 30, 2019, 4:45 PM I got email from Udacity with my syllabus. My experience might be beneficial for some one thinking to pursue the nano-degree in future. But also I want to express some of my concern about the course which might help Udacity to improve their course. I believe a lot of course material should be reviewed and the course need to be re-designed in couple of places. Let’s get started. …

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Writing software with a particular programming language for a while is like living with the one. The more you live together the more you know each other and also comfortable with each other. In the way, you kind of except the limitation, short coming and weirdness of that person. You also know the weakness and find a way to handle that.

But in the way you suddenly start to like someone and start to inspect all the new weirdness. Now its the same again discovering same thing (idioms, function, control flow, data structures, design patterns) from the beginning but in…

First of all Protocol Buffer (PB) has nothing to do with data analytics. But as I am very new to PB, I just tried to use my existing experience to explore PB and was able to figure it out successfully. Actually I already liked that concept of serializing structured data. To follow that document you do not need to be data scientist or data analyst but you just need to know about any RDBMS system and json way of structuring data. As I am going to explain PB thorough sql schema structure and python class.

To give a bit of…


Data Science and Data Analytics Developer

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