From DSS to Big Data: The Evolution of the Data Analyst


Take the centuries-old science of statistics, throw in the much newer — and rapidly changing —  discipline of computer science, and it’s easy to understand why the role of a data analyst has only increased in demand over the decades. Here’s a look back at the exciting and turbulent evolution of the data analyst:

1960s: The concept of analyzing data to increase business efficiency can be traced to the publication of Frederick Taylor’s The Principles of Scientific Management in 1911. But it wasn’t until the implementation of computerized Decision Support Systems (DSS) in the 1960s that the data analyst, as we think of the role today, first emerged. As John W. Tukey wrote in his 1962 paper The Future of Data Analysis, many statisticians, including himself, saw their interests shifting from pure statistics to “all the machinery and results of (mathematical) statistics which apply to analyzing data.”

1970s: The development in the early 1970s of Structured Query Language (SQL), a programming language designed to retrieve data from IBM’s database management system, altered the course of the data analyst position. SQL gave these specialists the resources to collect and manipulate large amounts of data and draw meaningful conclusions. The founding of the International Association for Statistical Computing in 1977 officially established data analysis as a methodology, acknowledging data analysts as “domain experts” who used their knowledge of statistics and computer science to convert data into information.

1980s: The introduction of the personal computer, as well as a shift in the business world to decentralized computing, significantly elevated the importance of, and demand for, the data analyst. In fact, many data processing departments had a massive backlog due to the shortage of data analyst professionals. (A related trend: The 1980s also saw the emergence of mobile technology that would lead to the development of smartphones and other modern mobile devices that have become huge generators of data.)

1990s: In 1994, Businessweek published a story on database marketing that essentially explained the purpose of the data analyst to their readers: “Companies are collecting mountains of information about you, crunching it to predict how likely you are to buy a product, and using that knowledge to craft a marketing message precisely calibrated to get you to do so.” The World Wide Web became a household term in the 1990s, and data analysts were suddenly in hot demand with companies frantic to extract meaningful information from the deluge.

2000s and beyond: The continued growth of the Internet, the social media revolution, and a reduction in storage system costs have all led to the accumulation of enormous amounts of unstructured information, or big data. The frenzied search for specialists capable of finding patterns and offering insights to companies has led to the data analyst being known as “the sexiest job of the 21st century.” Some data analysts take an even more specialized path, focusing on writing algorithms and code, or data mining (sifting through data to identify patterns). 

Data analyst salary trends

In 2015, a data analyst in the United States can expect to see an average salary ranging between $70,750 and $108,250, according to the Robert Half Technology Salary Guide. That’s a 6.1 percent increase over last year’s figures.

Today’s employers look for a data analyst to have:

  • Strong analytical skills
  • Relational database experience
  • Bachelor’s degree in an IT field
  • Database platform work experience (such as SQL, Oracle and IBM DB2)
  • Reporting tool experience (such as Crystal Reports)

With the number of social media and mobile applications only growing, companies are staggering under the weight of the data that’s increasingly available. This means data analysts continue to be highly sought-after by many employers, as these professionals have the skills needed to help employers use business intelligence and big data analytics to their advantage.

How do you think evolving technology will shape the data analyst job in the future? Share your thoughts in the comments below.