A visual history of data analysis tools

Let's take a trip back to the birth of data analysis to the unbundling of the data stack. In the past 50 years, how have analytics changed overtime and how to predict the tools of the future?

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Thibaut Collette

January 11, 2023 · 4 min read

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Over the past decade, data analysis has become a key component of decision-making processes in all types of businesses. But how has analytics become so important and indispensable? Well, it has a lot to do with the evolution of the tools that are used in this field: let’s see how these have changed and grown over time. 

The history of data analysis tools can be broken down into 4 periods. By the way, a short summary is available at the end.

Each era of data analysis tools

1970s - 1980s : The onset

Let’s start from the beginning, shall we? Here are the pioneers of data analysis and their groundbreaking innovations.

  • Edgar F. Codd: the “relational model” 
  • IBM: the business data warehouse 
  • Oracle: the mainstream relational database

2000s: The big data era 

The release of Linux was the starting point of many innovations during the first decade of the 21st century.

  • Postgres: a free and open source relational database management system
  • MySQL: an easy-to-use SQL engine 
  • Hadoop: parallel processing 

2010s: The cloud age

For the last 10 years, the importance of cloud computing  has skyrocketed, along with the number of innovations associated with it:

  • AWS Redshift: the cloud MPP data warehouse
  • Snowflake: the first fully managed SaaS platform for analytics 

These breakthroughs enabled the creation of a new process known as ELT (Extract, Load, Transform) – marking the beginning of the Modern Data Stack as we know it, and the birth of a whole new set of tools and cloud technologies.

2020s: The unbundling of the Data Stack 

These new tools have now become crucial for reporting processes in companies by enabling visualization, transformation, storage, collection, governance – and better decision-making. 

However, in order to reach their full potential, these tools need to be accessible for all data consumers – not only data scientists. This is why, at Husprey, we designed our Data Notebooks for everyone: let us help you bring the power of Analytics to your whole team!

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