Let's understand the basics with me

A Guide for the Data-Curious and the Data-Obsessed

If you are reading this right now, it means you have recognized your interest in Data.

At this point in time, you are or at least you wish to make career adjustments to ensure that 10 years down the line, your skills are still required in the job market.

And after listening to me speak about Data Analytics (obsessively), you have selected Data Analysis as your Uber ride into the Data World.

Buckle up, because I am about to take you on a wild ride of data-filled fun.

Let's start with the basics: What is Data Analytics?

• Let’s say your car gets stolen, you’ll hire a detective to solve the puzzle to discover “how, when, and who stole the car?” Data Analyst is much like a detective who solves a business problem by storing, organizing, and analyzing the data but instead of fingerprints and DNA, he/she uses data.

• It helps key decision-makers make strategic decisions based on data, rather than just going with their gut. Because let's be real, sometimes our gut tells us to eat a whole pizza, and that's not always the best decision.

• Data analysts play an important role in guiding core business units and practices, including marketing, IT, HR, accounting, sales, and business development. They're like the superheroes of data- they save the day and make sure the business is running smoothly.

And pretty soon, every company would dedicate you this song for being a Data Analyst😅

But what do Data Analysts actually do?

• Data warehousing: Just like our mothers who like storing old things and organizing wardrobes, a Data Analyst stores and organizes all the data.

• Data mining and visualization: They mine through the data to find hidden treasures and then create fancy charts and graphs to show it all off.

  

• Business analytics: They use data to figure out what's working and what's not in the business, like a personal trainer for your company.

• Predictive analytics: They use data to predict future trends and patterns, like a fortune teller with a Ph.D. in math.

  

• Enterprise performance management: They make sure everything is running efficiently and effectively, like a superhero sidekick.

Now, let's talk about the process of data analysis:

• Determine data requirements: This is like setting a goal for your data detective work.

  

• Collect data: This is like gathering evidence for your case.

• Organize data: This is like putting all the evidence in order. Now you know, how the “Sweater Hunt” was concluded.

  

• Clean data: This is like checking for any false leads or inconsistencies in the evidence. No wait Gopi, I didn’t mean -

  

• Analyze data: This is like solving the case and putting all the pieces together. Mama will be so proud of you, Adi.

  

And last but not least, the types of data analytics:

• Descriptive analytics: The Geet type - describes what has happened over a given period of time.

  

• Diagnostic analytics: This focuses more on why something happened. Think of it like asking yourself why you bought that fifth pair of shoes.

  

• Predictive analytics: This moves to what is likely going to happen in the near term. Think of it like predicting how much you'll regret that fifth pair of shoes when the bill comes in.

  

• Prescriptive analytics: This suggests a course of action. Think of it like telling yourself to stop shopping and start saving.

Why is Data Analytics Important?

Now jokes apart, let’s get real. You and I, both know the importance of Data Analyst and what we bring to the table.

A Data Analyst is like a GPS for your business- it keeps you on track and helps you avoid any potential roadblocks by helping you make informed decisions and stay competitive.

By analyzing data, companies can gain valuable insights into their operations, customers, and competition, which can help them improve performance, increase profitability, and stay ahead of the game.

Here are some specific ways data analytics can benefit different industries:

• Marketing: Data analytics can help companies identify key customer segments, track marketing campaign performance, and measure the ROI of different marketing strategies. This can help them optimize their marketing efforts and target the most profitable customers.

• Finance: Data analytics can help financial institutions detect fraudulent activities, reduce credit risk, and improve investment decisions. By analyzing large sets of financial data, they can identify patterns and trends that can help them predict future market movements and make better investment decisions.

• Retail: Data analytics can help retailers track inventory, optimize pricing strategies, and improve customer service. By analyzing data on customer behavior, they can identify which products are selling well and which are not, and adjust their inventory accordingly.

• Healthcare: Data analytics can help healthcare providers improve patient outcomes, reduce costs, and make better decisions about care. By analyzing data on patient outcomes, healthcare providers can identify patterns and trends that can help them predict which patients are at risk for certain conditions and take preventative measures to improve their health.

In short, data analytics is important in almost every industry because it helps organizations make better decisions, improve performance, and stay competitive in today's fast-paced business environment. With the increasing amount of data available to organizations, data analytics is becoming a critical tool for any company that wants to stay ahead of the curve.

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If you have read it so far, kudos to you for finally taking your life seriously.

All I ask is for is some action…

And if you need some help along the way, apka bhai haazir hai.

On that note,

Hafsa and Zain from Team Inspired Analyst - signing off!