Currently, most of the work done is massively based on digital platforms, automating the management of big data has become more essential than before. This is an aspect where Artificial Intelligence (AI) is being implemented by executing tasks more efficiently by copying the patterns of our abilities to learn and solve problems.
As technology keeps improving at a fast speed, empowered by the IoT environment, it has already set the pace for a synergistic relationship between Artificial Intelligence and Big Data.
Presently, digital consumer structure is more significant than before, providing the enterprise businesses with essential opportunities to target, market to, and enhance the lifetime value of customers.
Businesses that take complete benefits of big data and consumer data insights to achieve these goals are significantly positioned to stay ahead of the competition and prosper later on.
A Forrester report recently revealed companies that focus on the value of data “insights-driven businesses,” and they’re developed to control the competitive market. Those that prioritize data insights are increasing at an average of more than 30% every year, and by 2021, they will earn about $1.8 trillion.
How to Build an Insights-Driven Business Culture
Several of what fueled insights-driven businesses are technologies that enable them to process and analyze significant volumes of essential data at scale. But that’s only one piece of the puzzle. Most accomplished and successful organizations also build a business culture where these insights are maximized and regularly implemented to inform decisions and enhance processes.
Presently, lots of enterprise businesses these days are aware of the value of big data and consumer insights. Still, only a few are prepared to make all the essential changes to benefit from it.
Based on a recent global research report made by Cloudera, about 69% of enterprise organizations perceive having a broad data strategy as a requirement for meeting business objectives. However, only 35% think their present analytics and data management strategies are enough for this purpose.
Selecting the perfect management platform for your business needs is valuable, but there’s a lot more to developing an efficient enterprise data strategy.
Creating new methods for analyzing data
Due to AI, various ways to get insights have emerged into the market. AI has become the next step to query/SQL, formerly the methods used to analyze data. What previously used to be a statistical model has now converged with computer science and has already become AI and Machine learning (ML).
For example, though employees still play an essential role in data management and analytics, it is the tools like AI and ML that help the company analyze data effectively and speedily.
It will be rare to see a business person that wouldn’t prefer much better efficiency, reduced costs, and decreased risks in his/ her business operations? Several business leaders and investors generally agree that AI and Machine Learning could help simplify processes, hasten growth, and empower innovation.
Lots of companies have already realized this, and are speedily implementing AI-related technologies.
Analytics become more predictive and prescriptive
Lately, the CTO at Exasol, Mathias Golombek, stated in an EnterprisesProject article that, “AI is enhancing this analytics world with totally new capabilities to take semi-automatic decisions training data. It revolutionized the way you get rules, decisions, and predictions are done without complex human know-how.”
As a result, it is secure to assume that with AI assistance, Big Data has increased to epic and exponential proportions.
Prescriptive analytics, leveraging AI, can offer company comprehensive, strategic insights to help businesses improve further.
The data is still the data, but the means of getting insights on it will enhance, just as the combination of AI and big data is starting to disclose its possibilities.
Presently, there’s an abundance of important consumer data that businesses can use in optimizing their marketing and sales strategies. The volume of significant data is so great that customer data management technology is an important requirement for success. But that’s not the only thing enterprise-level businesses require in developing an efficient and effective data strategy.
Insights-driven businesses select accurate technologies for their goals and also develop internal processes to enhance their value. This includes building an organizational culture that regularly utilizes data insights to move transformation.