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Thinking in code

When learning a new foreign language, we typically start by learning basic vocabulary. Once we know a handful of words, we can start putting these words together into sentences. Long after learning basic vocabulary, grammar, and conjugation, we come to a point where we can finally think in a new language. It becomes second nature,…
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New to Programming – Learn, Help and Seek

Programming is always fun and it gives you an immense satisfaction of creating something new. If you are at the beginning of your career as a programmer, exciting things awaits you. Unlike most other careers, programming is easily accessible to gain some experience even before you start as a professional, thanks to the open community…
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Keys for Improving Predictive Analytics in Finance

Many companies spend months on budgeting processes only to have the budget become less meaningful as the new year begins and then the focus is about forecasting and budget changes. The directional outputs become talking points instead of actionable insights. In one case I was working on budgeting for fee income and the high-level, top-down,…
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Sharing Views

1. Come out of theoretical life and find a simple use case 2. Write down or brainstorm on the steps to achieve your problem statement, if you were to do this work manually, how would you do it? (Forget coding and syntax in this step) 3. Now divide these steps into components (one step at…
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Most common mistakes people make when working with data

What are some common mistakes people make when working with data? From my short experience, what I’ve encountered as the most common mistakes when working with data were (and still are): People not realizing that data needs to be cleaned, usually, but more frequently on academia, people with not much experience try to solve everything…
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Common mistakes when working with data

What are some common mistakes people make when working with data? When working with data, one should always keep in mind that data plays a very crucial role and ignoring it will just be doing “Garbage in-Garbage out”. We’ll find many people without the necessary real-world experience to fully understand the potential pitfalls we can…
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Bloopers to overcome when you start cooking with data

When starting to work with data, most people start with explainatory analysis instead of going through exploratory analysis. Psychology says that most people are focused on outcome rather than process, but in Data analytics its the process which is of utmost importance. Following are top three common bloopers: Lack of Curiosity : If you aren’t curious…
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Leaving Data on the Battlefield

Every data point is sacred. Every data point is great. If a data point gets wasted, decisions deteriorate! My team works to evaluate whether mental health programs make an impact on people’s lives. I lead a team of data sheros, and one thing I drill into my gals is that no soldier should ever be…
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What are some common mistakes people make when working with data?

We don’t just work with data. We socialise with data, we go to the cinema with data, and we have dinner with data on date night. We are surrounded and influenced by data 24/7, not just 9-5.  The mistake we make at all hours is blindly accepting numbers. When we see an interesting statistic, we…
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Common mistakes while working with data

Common mistakes while working with data: Cherry-picking: Selecting the results that fit your hypothesis and rejecting others Survivorship bias: Concluding an incomplete set of data, because that data has ‘survived’ some selection criteria Sampling bias: Trying to conclude the set of data that is not a part of the population under observation Ignoring Simpson paradox:…
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