Biz Tips: Continuous Intelligence for Continuous Innovation

Biz Tips: Continuous Intelligence for Continuous Innovation

Biz Tip:

Continuous Intelligence for Continuous Innovation

As businesses become more software-centric, the importance of real-time analytics is now more pronounced than ever. Some digital businesses have even shifted their business models to adapt to this change. The goal is now to deliver excellent, differentiated customer experiences to consumers who want everything “right now.”

What is Continuous Intelligence?

Continuous intelligence (CI), in one word, is automation. It’s not another buzzword that refers to real-time analytics data or throughput speed; it’s an approach that aims to automate access to and analysis of data so that it becomes seamless and continuous. CI is machine-driven and allows businesses quick access to data, no matter the complexity, volume, or diversity of data sources. By automating it via machine learning (ML), it becomes more than just a do-it-once-and-forget-about-it and turns into a set-it-and-let-the-machines-handle-it affair.

Because today’s consumers want “everything now,” businesses also want to see their data—and how it can help them—now. Data should be fluid and not stuck somewhere in a rigid IT dashboard if enterprise organizations are to experience a digital revolution. If analytics can’t help answer critical questions on the spot, then it becomes useless for businesses focused on revenue growth and leveraging on the digital revolution. CI is the logical solution, an AI-based solution that continuously interprets data, doing away with human bias and discovering patterns and anything of value within.

The Challenge of Big Data

The original idea of big data was to gather data from all internal and external sources into a single data platform where data could be wrangled into something meaningful. Instead of making the process smoother and friction-less, this added another step into the analytics pipeline: data wrangling. Putting all that data in one place backfired, however, because wrangling it took more effort than it was worth.

Ultimately, all the effort put into data wrangling was in vain because it took a huge amount of resources and effort to make the data usable. Businesses needed to create a separate wrangling module that was skills-dependent and slowed down getting the value from the wrangled data. By the time anything of value was obtained, the data stream would have changed so much that any perceived value is gone.

Instead of adding another step or module into the digital business workflow, businesses should take advantage of today’s powerful data-processing platforms and consider AI-driven analytics to automatically interpret and integrate data from diverse sources.

Continuous Intelligence Today

Today, leading financial services companies are starting to reap the benefits of CI by focusing on the right information, refining relevant signals, and acting upon them immediately. Most players in the CI field swear by four steps that help in pushing their business forward with data.

Market data validation

The need to capture the intra-day stream recording each market transaction and combine it with historically rich market data is vital in developing steps to maximize market opportunities. CI can help businesses stream enriched data to a real-time cache and historical repository where they can be analyzed as they come.

Trade, algorithm monitoring, and analytics

Today’s businesses need to monitor and manage market activity using real-time data in rapidly changing market conditions. CI helps companies adapt to constantly changing conditions using up-to-the-moment information and address challenges with specific, tailor-made solutions.

Real-time risk aggregation

As market volatility persists, there continues to be an increase in risk management systems investments. Risk management systems have been present for years, and today’s digital revolution demands their enhancement. Businesses today need a holistic view of their intra-day exposures, which means gathering data from the front office continuously and aggregating them into a consolidated view.

Compliance and surveillance

Today’s digital businesses handle a variety of sensitive data, making compliance and surveillance important issues, especially with consumers clamoring for more privacy in their transactions. Developers are now tasked to create sophisticated applications that can meet both regulatory and corporate requirements.

The “CI revolution” is not that far ahead, too. It is predicted that, by 2022, more than 50% of new business platforms will integrate CI into its systems, making real-time context data a major factor in making sound business decisions. Businesses should take advantage of how analytics and business intelligence teams can leverage CI to make smarter real-time decisions—and they should do it now. There is a huge opportunity in CI, but the time to act is limited.

Join The Rockstar Entrepreneur Community Now: Start Rockin Now

Similar Posts:

Leave a Reply

Your email address will not be published. Required fields are marked *