ABCs of Intelligent Analytics

Artificial Intelligence, Big Data Analytics and Cognitive Computing – these are the new ABCs of today’s big business. These evolving technologies are the foundation to a powerful emerging Analytics Economy, summed up as Intelligent Analytics.

In this very compelling economy, analytics, and how companies use analytics, is rapidly influencing how business gets done. Like the emerging technology principles noted in my last article, FastData, companies are leveraging the power and access to their data (of all types) faster than ever before.

Disruptors are becoming the norm, causing tidal waves of change and to remain competitive and survive in an increasingly volatile market, companies must rely less on instincts and more on Analytics. But companies must do so in a focused way. They need to identify the key areas that will make the biggest impact to their business, and this differentiation can be brought about by Intelligent Analytics.

What does Intelligent Analytics encompass?

Intelligent Analytics provides a versatile and sophisticated approach to unlocking performance improvements often trapped in complex sets of both historical and real-time data.

The suite of analytical techniques and algorithms automatically sift through volumes of data and discover insights that are often missed or undetectable by traditional statistical methods. Why? Think human bias. Statistical methods are inherently biased but Intelligent Analytics can be and should be inclusive of all data available.

There’s no single technology that encompasses Intelligent Analytics. There’s a variety of Advanced Analytics that can be applied to Big Data, but several types of technology work together to help you get the most value from your information.

Let’s review the most major players:

Data management. Data needs to be high quality and well-governed before it can be reliably analyzed. With data constantly flowing in and out of an organization, it's important to establish repeatable processes to build and maintain standards for data quality. Once data is reliable, organizations should establish a master data management program that gets the entire enterprise on the same page. 

Hadoop. This open source software framework can store large amounts of data and run applications on clusters of commodity hardware. It has become an essential technology for doing business due to the constant increase of data volumes and varieties, and its distributed computing model processes big data, fast.

Data mining. Data mining technology helps you examine large amounts of data to discover patterns in the data and this information can be used for further analysis to help answer complex business questions. With data mining software, you can sift through all the chaotic and repetitive noise in data, pinpoint what's relevant, use that information to assess likely outcomes, and then accelerate the pace of making informed decisions.

Text mining. With text mining technology, you can analyze text data from the web, comment fields, books and other text-based sources to uncover insights you hadn't noticed before. Text mining uses machine learning or natural language processing technology to comb through documents, emails, blogs, Twitter feeds, surveys, competitive intelligence and more.

In-memory analytics. By analyzing data from system memory (instead of from your hard disk drive), you can derive immediate insights from your data and act on them quickly. This technology can remove data prep and analytical processing latencies to test new scenarios and create models; it's not only an easy way for organizations to stay agile and make better business decisions, but it also enables them to run iterative and interactive analytics scenarios.

Predictive analytics. Predictive analytics technology uses data, statistical algorithms and machine-learning techniques to identify the likelihood of future outcomes based on historical data. It's all about providing the best assessment on what will happen in the future, so organizations can feel more confident that they're making the best possible business decision.

Beyond BI

Intelligent Analytics is a broad category of inquiry that can be used to help drive changes and improvements in transformational business practices. 

While the traditional analytical tools that comprise basic business intelligence (BI) examine historical data, tools for advanced analytics focus on forecasting future events and behaviors, allowing businesses to conduct what-if analyses to predict the effects of potential changes in business strategies. Predictive analytics, data mining, big data analytics, and location intelligence are just some of the analytical categories that fall under the heading of Intelligent Analytics.

Conclusion

Your Data, Your Advantage! Leveraging Intelligent Analytics offers distinct advantages compared to other means, especially when dealing with complex multi-process environments. The capability of Intelligent Analytics goes well beyond traditional means of statistical analysis. Its foundation in algorithmic methods removes the bias that is necessarily imposed by an individual analyst.

The goal of Intelligent Analytics is to allow the strategic leaders in business to be able to proactively sense and anticipate a situation before it becomes an issue or missed opportunity. Domain experts can then make informed decisions, build effective strategies and drive continuous improvement initiatives to take control of the situation.

I’m excited about the analytics economy because it creates opportunity for all to thrive and deliver on their business transformation objectives. Intelligent Analytics gives companies the ability to innovate, collaborate, change and grow in ways they never imagined. That’s why I love my role, partnering with companies to help them survive and thrive in today’s analytics economy by using Intelligent Analytics to make a big(data) difference.

About Mactores

Mactores delivers innovative, data integration, management, and support solutions. As an independent solutions provider, our success and strength are based on our core competencies in data science, data analytics, IT Support and Technology Transitions. We understand the complexity of today’s information systems platforms, that’s why we work to deliver the best solutions that align your organizational goals with your data.