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Stacy Gathu
Stacy Gathu

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The Ultimate Guide to Data Analytics: Techniques and Tools

The first time I heard the phrase data scientist will be the sexiest job of the 21st century, I was very intrigued. This is true as data is the new oil and data experts will be at the forefront of the discoveries of the century. One of these expert fields is the data analytics. So what exactly is data analytics?

Data analytics can be described as the science of analyzing raw data to make conclusions about the data which help inform decisions. This guide will try to give an analysis of the tools of the trade and techniques in data analytics.

Tools include programming languages such as Python and R. These come with a lot of libraries that help wrangle and manipulate data, do visualizations and develop models.

Business intelligence tools like Microsoft Power BI and Tableau.

Data Techniques include data collection, data cleaning, data wrangling, exploratory data analysis, feature selection, data visualization.

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M S N Karthik

Being from a PM background I have used all analytics tools like Mixpanel, Amplitude, Fullstory and also error tracking tools like sentry. Now, I'm working on my own product called zipy.ai - which combines product analytics, session replay, error monitoring both on web and mobile in one place. Do check it out and share feedback. Its an AI powered tool which helps in user behavior insights and auto fixing of UX issues.

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The Next Generation Developer Platform

Coherence is the first Platform-as-a-Service you can control. Unlike "black-box" platforms that are opinionated about the infra you can deploy, Coherence is powered by CNC, the open-source IaC framework, which offers limitless customization.

Learn more

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