Tracing the History of Business Intelligence (BI)

The idea of BI has been around for centuries, like a fine wine, it only gets better with age. The early 1800s saw organizations using simple tabular reports and graphs to make sense of their data. As the years went by, the world of business became more complex and the need for more sophisticated ways of understanding data became evident.

---

In the early 1900s, businesses stepped up their game by using mechanical calculators and punch card machines to handle and analyze massive amounts of data.

---

The 1950s marked the beginning of the Digital Revolution and it was then that BI finally came into its own as an independent scientific process. Entrepreneurs all over the world started to adopt it to inform their business strategies.

---

In 1956, IBM changed the game with their invention of the hard disk. It was a true behemoth with a storage capacity of 5MB and weighing over a ton.  This milestone was more than just impressive, it was a game-changer for BI. It paved the way for physical filing systems to be replaced by digital ones, and it was a true turning point in the history of data management.

---

In 1957, FORTRAN made its grand entrance as one of the first major programming languages. Developed by IBM for scientific computing, it was the ultimate tool for low-level access to the inner workings of the computer. While it may seem basic today with only IF, DO, and GOTO statements, back in the day, it was the bee's knees. FORTRAN also introduced basic data types such as logical variables (TRUE or FALSE), integer, real, and double-precision numbers, which are still widely used today.

---

---

As much as FORTRAN was good with numbers, it didn't have the best input-output game. That's where business computing comes in. Business computing started to take off in 1959, and to cater to this, COBOL was developed. It was a language that was tailor-made for businesses, and it was the perfect complement to FORTRAN's number-crunching capabilities.

The introduction and use of computers skyrocketed in the 1960s. Back then, computers were expensive, required a team of experts to operate, and extracting data from them was a real pain in the neck. The real kicker was that we didn't have any centralized way of bringing all the data together, so it was all just a big data dump.

---

---

As they say, every problem is an opportunity in disguise. Enter hierarchical Database Management Systems (DBMS) like IBM's IMS, which took data organization to new heights. These systems were based on binary trees, where data was arranged in a hierarchical tree structure of parent and child records. And the best part? It resulted in data independence, security and integrity, making data searches a breeze.

---

Furthermore, the 1960s saw the emergence of advanced data analysis techniques such as multidimensional analysis and online analytical processing (OLAP), which revolutionized the way organizations analyzed and understood data.

In the 1970s, Ted Codd revolutionized the way we store and access data with his game-changing paper "A Relational Model of Data for Large Shared Data Banks". He single-handedly coined the term 'relational database' and paved the way for the development of the most widely used databases today. He truly made data organization more efficient, flexible and user-friendly. Thanks to him, we can now enjoy the ease and convenience of popular systems like MySQL, SQL Server, and PostgreSQL. And let's not forget SQL, the standard language for manipulating and retrieving data, all thanks to Codd's ingenious idea.

---

As businesses started leveraging multiple databases to store diverse information during this time, the need to merge this data became imperative. ETL (Extract, Transform, Load) emerged as the go-to solution, streamlining the process of acquiring data from various sources, molding it to fit the desired destination format, and loading it into the target destination. This approach quickly became the industry norm for consolidating data from multiple sources.

---

Additionally, in the 1970s and 1980s, BI systems started to become more accessible to smaller businesses, thanks to the development of personal computers and the proliferation of user-friendly spreadsheet software like Lotus 123 in 1983, and Microsoft Excel in 1985. This made data collection, storage, and analysis a breeze for businesses of all sizes, and helped drive the growth of BI. It was like giving small businesses the keys to the castle, they now had the same tools as the big guys to make data-driven decisions.

---

---

During this time, graphical user interfaces (GUIs) and intuitive data analysis tools made BI systems easier to use. This led to widespread adoption and becoming a vital part of organizations.

---

The emergence of the World Wide Web in the 1990s was a defining moment in the database industry. As more businesses invest in online initiatives, the demand for sophisticated client-server databases grew. Stage right, enter the World Wide Web. In 1995, this technological miracle sparked an explosion of growth in the database sector and gave birth to an open-source gem, MySQL. MySQL disrupted the status quo by offering an alternative to the proprietary systems supplied by Oracle and Microsoft, and it remains a popular choice among many to this day.

---

In the 1990s, data warehousing emerged as an important innovation in the field of business intelligence. Data warehousing included the collecting and storage of data from numerous sources in a concentrated location. This made it feasible for corporations to examine data from several sources and acquire previously impossible insights. ETL was essential to data warehousing, since it was used to extract data from several sources, convert it, and load it into a data warehouse.

---

Finally, the rise of "big data" and cloud computing also began in the early 2000s, as advances in storage, processing power, and technologies such as Hadoop and virtualization enabled enterprises to collect and store massive volumes of data, and cost-effective IT solutions became more in demand.

---

---

Additionally, BI data analysis and reporting tools such as Business Objects, MicroStrategy, and Cognos surged in popularity, as did data warehousing solutions like Teradata. The era of big data and cloud computing began.

---

Today, business intelligence (BI) is an important part of many organizations. The development of data visualization tools such as Tableau and Power BI helped make BI more accessible and user-friendly.

---

---

New technologies like artificial intelligence (AI) and machine learning play a big role in how data is analyzed and used to make decisions. BI has come a long way since its early beginnings, and it continues to evolve and shape the way organizations operate and make decisions.