In 2017, the Advanced and Predictive Analytics Market Study published by Dresner Advisory Services resulted in an increased interest in predictive and advanced analytics, with data scientists, statisticians, business analysts and business intelligence experts being the most prevalent early adopters.
What every business owner should know is that the advancement of predictive analytics significantly affects business intelligence.
But, how?
Read on to learn more about the role of advanced and predictive analytics in business along with how 5x Technology can help with your BI solutions.
The term "advanced analytics" refers to data analysis that is much more than just simple mathematical calculations, such as averages and sums or sorting and filtering. It uses statistical and mathematical algorithms and formulas to create new information, predicts outcomes and even recognizes patterns, as well as any respective probabilities.
The other term, "predictive analytics," is an advanced analytics subdivision and focuses on identifying future values and events and their respective probabilities.
The current age of digitalization and information has brought some new methods and technologies that can improve business operations while helping to maintain a competitive advantage. These include:
With this in mind, consider the following key takeaways from the report and how they affect current and future businesses.
The report shows that modern companies are incredibly pragmatic when it comes to their investments in BI technologies. Video analytics, the Internet of Things, text analytics and cognitive BI, are still in an emerging growth state. With Crystal Reports and SAP training, you and your team will have the skills necessary to create and implement every aspect of your business intelligence solution.
The apps support traditional statistical methods, which include analytical functions, hierarchical clustering, and regression models. These top three features are considered to be crucial by about 80 percent of enterprises that were surveyed during the study. The next most required series of features include geospatial analysis, Bayesian methods, automatic feature selection and recommendation engines.
Consulting and business services most often rely on geospatial analysis, hierarchical clustering, textbook statistical functions and regression models to create a strong business case for BI. The survey discovered that the manufacturing and transportation industries trail in the majority of categories and respondents from wholesale and retail companies care the most about video analysis (which is new for 2017) ensemble learning, neural networks, and Bayesian methods.
Another interesting finding, according to the survey, is the fact that relying on an abundance of predictive analytics features won't always lead to successful BI strategies, but focusing on the outcome of the business will. As a result, more and more businesses are prioritizing the traditional textbook statistical functions for the descriptive statistics, automatic features selection, recommendation engines and other advanced features when they start making a BI strategy.
With the above findings in mind, it is crucial to now begin thinking about these factors for your own business. Each tool, every year, along with all the analytics involved create their unique challenges, but as long as you are continually improving your business intelligence strategy, you can expect your business will grow and develop alongside your plan.
Which parts of your business intelligence can use an overhaul? We challenge you to walk through and record the experience from a buyer's perspective, and it will become clear what needs improvement.