We have seen tremendous progress in the Information & Technology domain in recent times. The tech ecosystem has achieved many revolutionary feats, and new terms such as data and analytics have been introduced to the common man in the last two decades. These two terms are currently evolving and reshaping businesses in the market.
Today’s businesses rely on data to know about their customers and competitors and understand the overall market and remain competitive in the marketplace. Hence, with the advancements in technology, the number of companies interested in collecting data has grown substantially well. The interest in data for entrepreneurs and business owners has led to increasing demand for experts with relevant education to analyze and interpret that data.
To understand the evolution of the data, analytics, and insights industry, and to learn how today’s businesses use data, read further:
History of analytics
The history of analytics goes back to the 19th century when business analytics emerged in the late 1950s. The tools that were developed could capture information and identify patterns and trends faster than the human mind. IBM invented a hard disk in 1956 that gave the push for the analytics movement and set the stage for companies to find the substitute for physical filing systems with digital ones. The early efforts at business intelligence are often referred to as Analytics 1.0 by data analysts.
The analysts used to spend more time collecting and preparing data and for descriptive reporting. It was mostly for internal data sources like batch processing operations. The early era of business intelligence lasted for about half a century, till the advent of big data in 2009.
Big Data era
It is the time when search engine giant like Google and social media giant like Facebook started their operations. They identified and began collecting and analyzing a new type of data called “big data” in the mid-2000. The term big data took ten years to get recognized in the common man’s dictionary.
Analytics 1.0 was generating the internal operations and transactions data of the company but, the new set of data, i.e., big data, came from external sources. They generated these sources from the public data sources, specific projects like the Human Genome Project, and the sources are drawn from the internet also. Hence, the big data era is also called Analytics 2.0.
With the switch from Analytics 1.0 to 2.0, we have witnessed a significant change in business operations. The new technologies and processes helped companies and businesses to turn data into business insights and benefited in generating more profits. It has influenced the strategic business decisions as the data analysts of the Analytics 2.0 era were better equipped than their former counterparts in applying advanced technology tools.
Evolution of data analytics and insights
With the introduction of smartphones, the third era of analytics was short-lived. Due to social media evolution, the data collection tools and personalized user experience tools required an upgrade, so Analytics 4.0 has arrived. Now, we are relying on cloud technologies and advanced automated decision-making tools. Today, organizations have more ways to collect customers data and other relevant inputs. They collect data from websites, social media channels, mobile applications, customer phone calls, live chats, surveys, and more. Apart from these, companies also gather data through location-based advertising, loyalty programs, and digital marketing campaigns.
New analytics provides predictive and prescriptive analytics data. It equips the business executives with the insights of a future event and recommends possible courses of action. It also offers real-time insights through analytical applications to support their decision-making.
The future of analytics
It is not an end to the technology revolution and analytics evolution. The fourth era of analytics is run by machines and managed by intelligent technologists. There will be no more manual interventions necessary with just an AI-powered system to guide our personal day-to-day activities in the near future. Only time should tell which technologies will make a giant leap and get humans to adjust to it.