The origin of the term Big Data is as perplexing as the phenomenon it describes. In his attempt to track down its etymology, New York Times journalist Steve Lohr searched through databases of digitally-stockpiled emails, documents, presentations and lectures shared among economists and technologists and librarians. In other words, it was necessary to dig deep through Big Data in order to make sense of the history of Big Data.
In modern parlance, the phrase has come to mean a massive quantity of data drawn from a wide array of sources and organized in diverse silos to be used for any number of purposes through the application of innovative and evolving processes. As we might say of most modern relationships: It’s complicated.
Consequently, discerning insights from Big Data can be an overwhelming if not impossible task for the human mind alone to accomplish. Fortunately, the human mind has invented a way to get at these insights without pulling any muscles: automated data analysis.
According to Gartner, more than 40% of data science tasks will be automated by 2020. Through augmented analytics, businesses can employ machines to capture the key insights that human data scientists aren’t capable of mining out of the masses of data.
That’s not to say that there are no humans left in data analysis. As Cameran Hetrick, Senior Director of Data Science & Analytics at thredUP, told The Innovation Enterprise, “Analytics and algorithms will always need to be managed by a person. Sure, there is a lot of automation that can be done to remove the human touch, but we will always need an analytics person to translate a business question into data questions and data results into business strategy. A human must be involved to construct an algorithm and manage it to ensure that it meets all the goals of the organization.”
All businesses – and even departments within a single, large enterprise – have unique goals and operational procedures. While machine learning and augmented intelligence make it easier to automate data analytics, human experts are still necessary to generate the questions that will help businesses achieve their goals. Human analysts are still needed to translate data insights into actionable improvements in operations.
Automating data insights transforms business culture. It increases productivity, reveals previously hidden patterns in consumer behavior, and eliminates guesswork and personal bias in business decision-making.
At Antares, we help you collect, process, and store valuable company data and introduce tech-savvy strategies for surfacing that data through dashboards and scorecards for easy review and monitoring. By integrating, simplifying, and consolidating your valuable business information, processes and workflows through robust Enterprise Applications, we increase your human potential. Contact us today!