There is a lot of talk among IT professionals of big data issues, and discussions at many business conference tables center on how the organization might find greater benefit and advantage from the intelligence buried in the business systems and information. It is a two-part problem, where the collection and the analysis each play essential roles in developing real business intelligence.
“So what’s getting ubiquitous and cheap? Data. And what is complementary to data? Analysis. ..” Hal Varian, Chief Economist at Google and emeritus professor at the University of California, Berkeley
The information technology and systems in a business support the operation. Software and computers help people do their jobs, and the information collected in and generated by those systems becomes the foundation for developing business “intelligence”. Today, businesses must reach beyond their own direct operational support systems and consider the full realm of data to be collected, including IoT sensor data or social media data.
Business intelligence is gained from the analysis of the business data – analysis which helps owners and managers make better and more informed decisions which are based on data and not emotion or “gut”.
Business intelligence was a term popularized in the 1990s, but the key was the analytical component (business analytics), which gained focus in the late 2000s. Today it is big data and big data analytics, where organizations are working with massive data sets not previously even imagined.
The volume and velocity of information collection is ever-increasing even in the smallest of businesses, creating a great need for tools which can structure and correlate data so that it might render some insight. Simply storing and managing these huge and growing data sets becomes problematic when conventional technology models are applied.
Among the more significant challenges facing businesses is how to efficiently support and enable the “science” of big data, while providing the confidence and maturity of more traditional and often better understood infrastructure services. What was once purely in the realm of IT is now delivered directly to the analytics consumer in the form of infrastructure as a service, changing entirely the once-rigid boundaries of IT management forever.
Once the business has the data, then it must find a way to analyze the data, which generally involves also applying visualization tools. Many IT departments are feeling pressured to develop new skills and capabilities around data collection and management, yet it is more frequently the business user who provides the analysis and applies visualization tools to the task.
Data collected by the Aberdeen Group, found that employees in organizations that used visual data discovery were more likely to find the information they need when they need it. Additionally, these same companies were able to scale their use of scarce IT resources more effectively.
Mendelson Consulting and the Noobeh cloud services team work with Microsoft Azure SQL, Data Warehouse, Data Lake, Data Factory and Microsoft Fabric to provide businesses with the scalable, flexible and agile infrastructure they need to collect, transport, transform and store the data from which intelligence and insight might be derived. Connecting to Power BI and other solutions enables visualization and pattern identification that not only informs human decision-making, but AI learning as well.
The use of business intelligence and advanced analytics continues to grow in every segment of the market – from small business to enterprise – and plays an increasingly important role in supporting business success.
Most businesses don’t have the technology or the data to enable significant quality or business transformation. But times are changing, and deployments of data collection, analysis and visualization software and tools are expanding.
This is a fundamental aspect of business digital transformation and fuels the next step, where intelligence is applied to conditions revealed in the data and activities are automatically performed guided by that intelligence. This is where AI starts.
