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Join me in this article as I briefly deep dive on what I think are the 7 Essential Tools for Data Analytics and Digital Transformation.

The are a bunch of tools, software, courses and it is easy to feel overwhelmed, but don’t worry, I will share with you the basic tools you need to know to start this journey.

7 Essential Tools for Data Analytics & Digital Transformation:

• Smart Spreadsheets – for fast data manipulation and prototyping.

Yes, you read it right. You need to know at least Microsoft Excel or Google Sheets basics. Why? because you are about to enter in the area of data manipulation, prototyping, understanding a data base structure and doing calculations.

You should at least get familiar with basic formulas such as the ones for descriptive statistics (Don’t get scared when reading “statistics”) such as mean, max, min, sum, median, etc.

When begging in the Data Analytics world you will need to start with a basic spreadsheet, nothing too fancy or that require sophisticated IT skills.

You should aim to get confortable understanding tables of data in a tidy structure that could be later analyze.

• Low-Code Development Platforms – to build apps and automate workflows with minimal coding

To analyze something, you first need to gather the data! So, here’s were the low-code development platforms enter the game.

What are low-code platforms? Is software that it is easy to code and program Mobile Apps.

Imagine you have an inventory process, and you want to determine if something if reprocessed from the inventory picked and then make any changes as this is causing noise and disturbance on the process, however you lack data to make an inform decision. Maybe modifying the company’s ERP won’t be viable. You want to create a quick low-code platform to gather data to later analyze it.

Some examples of low-code platforms:

• PowerApps
• Google Appsheet
• Microsoft Forms and Google Forms – These are the most basic ones, but it is a good shortcut to start gathering data from your processes.
• Business Intelligence Tools – to visualize, analyze, and report data in real-time

Have you heard of Tableau, Power BI or Looker? No? well, you should start learning about any of these. Which one? I highly recommend starting with the one that you will have access in your organization.

Here is my best pick: Power BI; Why? I consider this has the best information out there to start creating reporting and dashboard, you will be able to learn the basics of data structure, BI, data management. And if you later want to jump to a different software, you will have a good foundation. My best example for this is my Fiancée, she learned PowerBI and then did the jump to Looker. The transition was smooth and she is doing good reporting in her organization.

You should at least get familiar with one of these software and start ‘playing’ with the reports already created in you organization.

• Process Mapping Software – to visualize operations and identify improvement opportunities

I have found on several occasions where a lot of reworks is made because of a poor process oriented mindset and lack of standardization.

I recommend Visio or Flowchart to start mapping process where data flows or process within your organization.

• AI-Powered Chatbots – for automating user interactions and quick data access. And for guidance.

I made a lot of Python, R and even SQL code without the need of fully know the language, just the basic principles, and understanding the logic behind, and with the help of chatbots I have been able to create sophisticated reporting. Also it is good to use when you hit a wall and don-t know what to do.

• Cloud Databases – to store, manage, and query large-scale data efficiently

This are once you are moving deep in the data analytics world. And eventually move from Excel databases or Access to SQL or cloud data bases.

• Data Cleaning & Prep Tools – to ensure quality and consistency before analysis

Finally, but not least. Data cleaning is one of the most important tools you need to know. You will need to be able to determine whether your data is accurate and it is free of typos and errors.

Python is one of the most recommended tools to learn to start doing this, but if you are starting, just keep with Excel (I recommend looking information about PowerQuery and PowerPivot)

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Hope this post help you through this journey.

If you have any questions, I’m open to start a conversation to guide you.

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