BI to AI in Next 7 Years
January 19, 2019
January 19, 2019
Data on its own doesn’t solve anything
Business intelligence (BI) is a technology-driven process that analyzes data and presents it as actionable information to top management and the boardroom. It aids decision makers in understanding the real state of the business per time and make better business choices.
Lately, BI has evolved into three broad fields:
- Descriptive analytics: this branch of BI summarizes raw data into a human-readable form. As the name implies, it describes the past using a wide range of historical data, draws comparisons and attempts to understand how the data can influence the future.
- Predictive analytics: this branch of analytics is used to predict unknown future outcomes using patterns from past causes and results. Although predictive analytics is incapable of producing a correct (100%) outcome, it utilizes probability to predict “best possible outcomes,” it is particularly effective for mathematical models.
- Prescriptive analytics: this AI-powered branch of BI encompasses both predictive and descriptive analytics. Like dynamic programming, it makes optimal trade-offs between required outcomes and constraints using logic and mathematics.
How companies can transform their BI strategies to AI to get more intelligent insights
According to Michael F. Gorman, professor of operations management and decision science at the University of Dayton in Ohio, the problem with BI is that “It doesn’t tell you what to do; it tells you what was and what is.” BI is data without insights. Here is how companies can leverage on AI to transform BI analytics for maximum benefits:
- Automate decision making: having all the data about the business staring at you from dashboards and data charts is not enough. Decision making should be automated to enhance long-term strategic plans, with insights generated by AI from BI tools. This would save time and free up human resources for tasks that are human-centric.
- Structure your data: you have probably heard that information is the new oil. Big Data has been growing at an exponential rate for the past two years. Most of it is unstructured; and If left unstructured can become a cog in the progress wheels of most firms. Enterprises must be fully digitized. It takes more time to glean insights from unstructured data using machine learning algorithms. New AI-powered BI tools have this capability.
- Get real-time insights: due to advancements in AI, BI tools can provide insights in real-time. Sparing executives, the hassles of sifting through pages and dashboards to uncover trends.
How Big Data has changed the world in the past decade
More data has been generated in the past two years than in the previous 7,000 years. Connected mobile phones and IoT devices are predicted to peak at 20.4 Billion devices in 2020 according to Gartner. Things will never be the same again. Here are three ways Big Data changed the world in the past decade.
- Personalized and targeted adverts: though this deserves an article of its own; using big data collected over time, tech giants like Google and Facebook now show their consumers adverts that match their exactneeds and thinking patterns. When consumer traits used are demographics like race, economic status, sex, age, level of education, income level and employment, etc. The advert is presumed to be targeted. When indices center on lifestyle, websites visited, political leaning, morals, values, opinions, and attitudes, etc, the ads are personalized. Targeted and personalized adverts are very effective. It was reportedly used by Cambridge Analyticato influence political outcomes in the US, UK, India, and Nigeria. We often make compulsive purchases influenced by personalized adverts without even realizing it. Some have argued that big data poses a threat to liberal democracy.
- Smart Cities: using data collected from IoT devices, governments around the world are building smarter cities. Los Angeles recently replaced streetlights with LEDs that self-report when they stop working. According to the BBC, Songdo a city in South Korea, has been designed with sensors to monitor temperature, energy use, and traffic flow. These sensors can – in theory – alert you, personally, when your bus is due. Alternatively, let the local authority know about any problems.” More and more cities are becoming smart with big data.
- Security and governance: the NSA and counterpart organizations have access to vast global data, that they use to fight criminals, scatter terrorist plans and spy on other governments. Although cases of such thwarted terrorist attacks are often not publicized. Officials are also using data from BI dashboards to make better decisions and keep a pulse on the city. Deploying resources where it is most needed.
How big data alongside AI will change the world in the next 7 seven years