With numerous ways to transfer and process information, we have witnessed the dawn of the digital era. We have seen data being shared via text, images, videos, and various other forms. Data has changed the way business is being done. It has changed the entire enterprise paradigm. Moreover, from the last decade, the usage of technologies like machine learning and artificial intelligence has been widespread. AI has transformed the way we live, work, and shop in many different ways.
Realizing that answers to most of their business challenges lie in data, companies are now turning to machine learning and AI by supercharging performance and implementing innovative solutions to address complex business problems. The combined power of AI and ML is improving the ecosystem of business intelligence which is essential for making insight-driven decisions.
With business intelligence, enterprises receive faster and more accurate reporting as well as analysis. They tend to make better business decisions, improve employee satisfaction, and enhance data quality. They are able to get a 360-degree view of their business which makes it easy for the decision-makers to visualize problems and take proactive actions to resolve them before the situation worsens.
BI is embracing features and capabilities that fuse machine learning and artificial intelligence with traditional BI offerings. With advanced predictive analytics, BI is transforming from providing traditional queries and reports to allowing users to understand trends and future possibilities, predict possible outcomes, and make recommendations. This changes the conventional role of BI of answering, “what happened”, to an AI-driven BI that answers questions like what will happen next, and what measures should be taken in the future.
Tools like Tableau, Power BI, Qlikview, Microstrategy, Logi Analytics, and Splunk prove that with the combinational power of ML, AI, and BI, businesses can achieve a lot in lesser time and with less effort.
Analytics helps companies to transform raw data into operational reporting insights to reduce decision-making based on intuitions. With vast amounts of data at your disposal, more decisions will be rooted in data analysis than on instinct. However, data-driven tools often require manual development processes to aggregate sums and averages. The findings derived by such analytics methods often lack a holistic reflection and do not generally put statistical significance into consideration. Models developed by leveraging AI and ML facilitate automated learning with less or no explicit programming. This gives businesses the ability to efficiently analyze enormous volumes of data that may contain too many variables for traditional statistical analysis techniques or manual business intelligence.
Machine learning algorithms, when trained properly, automatically discover the signal in the noise, and eliminate the possibility of getting insights that are erroneous. It becomes easier for users to detect hidden patters and trends lying in their data.
Over time, this trained model can teach itself to become more accurate. The model then adapts itself whenever new data is introduced.
Perceptibly, businesses are more interested in outcomes and actions as opposed to mere data visualization, interpreting reports, and dashboards that show them how they did in terms of sales or revenue. Hence, by adding an element of machine learning and AI, businesses not only get insights into historical data but also get an answer to “what next”.
The power of machine learning and artificial intelligence goes beyond understanding what has happened to offering the best evaluation of what the future holds. Classification algorithms, specifically, form the foundation of such predictions.
Advanced algorithms are trained by running specific sets of historical data through a classifier. With the help of behavior patterns from the historical data provided to train the models, ML algorithms determine how likely it is for an individual or a group of people to perform specific actions. This facilitates the anticipation of events to make further decisions.
The principal goal of business intelligence is to provide decision makers with the capability to better see the relationship between trends, patterns and behaviors for better decision-making and optimization of resource like budget and people. At Stridely Solutions, we offer you the optimal BI services powered by AI and ML.