Part one of our blog series explored how people are the driving force behind the digital transformation and how it is fueled by artificial intelligence and machine learning. We also took a first look at how fp&a and business intelligence professionals can start to derive tangible value from these technologies for Enterprise Performance Management. Now, we will take a deeper look into AI, Machine learning and other trending technologies and the evolution of data analytics from descriptive to prescriptive.

Analytic Evolution in Enterprise Performance Management

About 15 years ago, Enterprise Performance Management (EPM) was introduced as a subdivision of Business Intelligence (BI), a new concept that addressed the growing complexity and problems with managing business performance through spreadsheets. First-generation EPM software tools enabled normal business users to view their data from various angles and store it safely in a database specialized for flexible planning, analytics, and reporting. Compared to today’s standards, analytics was often limited to trying to describe past events, hence the name, descriptive analysis.

Since that time, the amount of data has skyrocketed while processing power has soared and storage options have dropped in price. Advanced analytics responds to next-generation requirements. It quickly processes large amounts of data from internal and external sources, so users can recognize patterns and gain deeper insights to make better decisions.

Predictive analytics is one aspect of advanced analytics that will be key in driving efficiency and innovation. It runs statistics and algorithms (also known as data mining) on masses of historical data to calculate probabilities and future events. Modern-day forecasting, for example, relies heavily on predictive analysis.

Going forward, we will increasingly see BI and Enterprise Performance Management tools for financial planning and analysis that support customers with AI augmented capabilities to predict future business outcomes and recommend actions to improve them. This is known as prescriptive analytics.

Types Of Artificial Intelligence Infograph

Types of Artificial Intelligence: Machine Learning, Deep Learning

Analytic Revolution with Artificial Intelligence and Machine Learning

Even outside of the world of business intelligence and EPM, there is a tremendous buzz about analytics, artificial intelligence, and machine learning. Artificial intelligence (AI) is any technology that allows a machine to mimic human intelligence, meaning it thinks and understands the world like a real human being. The concept of artificial intelligence has been around since the late 1950’s, but quickly lost relevance because the time was simply not ripe.

With the sheer unlimited availability and the downward pricing trend for processing power as well as the masses of data waiting to be analyzed, AI is no longer something out of science fiction novels or research labs. The possibilities for utilizing artificial intelligence are seemingly endless. Artificial intelligence will be the real game-changer for not only businesses but also society as a whole over the next decade.

Machine learning is currently driving most trailblazing innovations in AI. It encompasses specific algorithms that enable a computer to process information, derive findings, and then apply them as part of an ongoing improvement cycle. This means that people no longer have to program a computer to perform a very specific task. Instead, computers can teach themselves to make decisions and solve problems on their own.

Machine learning and especially its sub-division, deep learning, however, require a plethora of good data on the scale of Google or Amazon. It is also the “fuel” behind futuristic breakthroughs such as self-driving cars. Simply put, it is extremely(!) advanced analytics.

GPU Accelerated Computing and Data Integration Technologies support AI

At Jedox, we are also augmenting our software platform with AI and machine learning capabilities. Today, our clients in fp&a and other lines of business are using the flexible, collaborative Jedox software platform to align budgets, plans and forecasts between finance and operations.

Jedox is in a unique position to power Artificial Intelligence with GPU accelerated computing which provides additional steam for faster processing and analytics of large data sets beyond the high-performance in-memory database engine. The Jedox data integration tool and pre-built connectors make it easy to merge data from multiple sources. The Jedox Integrator brings together data from internal systems such as ERP and CRM and joins it with external data source to identify the most relevant drivers and trends.

Jedox GPU Accelerator

Jedox GPU Accelerator

We’ll talk more about how the Jedox AI engine enables next-generation business intelligence, financial planning and analysis, automation and validation of the sales forecast and sales plan and many more specific customer use cases in Part 3 “The Future of Enterprise Performance Management is Dynamic” of this blog series.

Watch the new Video Trailer on AI and machine learning in Enterprise Performance Management for BI and FP&A