Big data is big news across industry sectors. The digital age has given rise to information overload, and the most resourceful businesses are learning how to take advantage of that information. It takes a special type of skill to gain actionable insights from these massive amounts of data, and that is where advanced analytics comes in. With technologies like artificial intelligence (AI) and machine learning (ML), data-driven business insights are possible like never before. Here’s a breakdown of how these technologies really work.
The Science of Advanced Analytics – Traditional analytics refers to more linear quantitative analysis, usually generated by business intelligence (BI) systems. These are examinations of performance drawn from a structured and pre-defined framework. They use existing historical data from a database or data warehouse.
With advanced analytics, we are able to follow the data without a pre-determined scope. All you need is a starting point. For example, consider the question: what type of people buy yogurt in the mornings? With traditional analysis, you would be left skimming through sales data and designing reports to cross reference yogurt sales and time of day, but that only tells you how many people have performed this action, not what type of people they are. Using advanced analytics, a company can mine the relevant data to identify the correct market segment. This could have real world applications for which advertising time-slots they purchase.
Advanced analytics can also utilize a broader range of data. Traditionally, structured data has been the most useful. Social posts are hard to manage in a report; how do you quantify someone’s verbal review? With advanced analytics, unstructured data like this can be incorporated into the analysis to determine the most comprehensive data-driven conclusions.
You need some pretty powerful tools to utilize advanced analytics. We’re talking about mining massive amounts of data and making connections to create actionable insights. This is where artificial intelligence and machine learning come in.
What do we mean by Artificial Intelligence? – The term AI might bring to mind images of rampaging sentient robots, but never fear, these days AI looks a lot different (and a lot more useful). The essential concept is the same, though. AI refers to a non-biological processing power (i.e, computer) being able to learn and adapt through processes similar to biological neural pathways. Our brains respond to new information by creating new neural connections, and these connections (pathways) are reinforced by repeated use. Similarly, artificial networks have the capability to respond to inputs by changing their processes, perceptions, and functional patterns, effectively creating new pseudo-neural pathways.
Machine Learning; Algorithms that Evolve – Machine Learning (ML) is an example of AI in action. It is a type of algorithm that learns from its experience and “evolves.” A traditional algorithm is designed as a closed framework. It is designed do perform a task or solve a known problem. While the solution and results might vary for these algorithms, the underlying code will remain consistent. A machine learning algorithm actually rewrites itself as it encounters new and pertinent data. This means that as it gathers information, it is able to make itself more efficient and more accurate as it goes. They follow the data without prejudice, and so can identify complex corollary relationships that would be nearly impossible for a human to predict, let alone find.
Advanced analytics are an exciting area of exploration for businesses these days, enabling more targeted analysis. This opens up the field to much more complex data exploration and can go along way toward helping identify more pertinent causal relationships in business performance. Advanced analytics with AI and machine learning can take any company’s data strategy to a new level. Dobler Consulting is a full spectrum database service with 10 years of experiencing helping companies strategize and execute workload management solutions. For more information about Dobler Consulting and how we can help you plan and implement advanced analytics into your data strategy, visit DoblerConsulting.com or call us at +1 (813) 322-3240 (US) /+1 (416) 646-0651 (Canada).