The Most Important Types of Business Intelligence Technologies In 2019
If you want your business to stay on the leading edge, you need to invest in business intelligence technologies. This has become even more apparent in 2019 as technology has advanced.
No longer are we struggling with the gathering and storage of data. Now, we’re more capable than ever of gathering relevant, quality data. We can then make reliable business decisions through analytics.
Read on to learn about the most important business intelligence technologies of 2019. Leveraging these technologies will increase your company’s success!
What are Business Intelligence Technologies?
Business intelligence technologies help decision-makers – executives, managers, and analysts – make informed decisions. The amount of technologies available has exploded due to inexpensive data storage costs.
IT departments used to run complex reports to crunch all this stored data. Business intelligence technologies are now capable of analyzing big data. They easily create meaningful insights.
2019 is all about business intelligence customizability. Companies want tailored solutions that seamlessly fit within their business processes. Data presentations need to be clean and easy to digest in order for decision-makers to be at their most efficient.
Data Quality Management (DQM)
The ability to gather large swathes of data has grown. This also means the need has grown to develop software that sifts through data and eliminates low-quality reports.
Companies are starting to recognize the quality of their data matters just as much as the quantity. Eliminating data blindness is an important part of managing data.
More companies are investing in improved data quality management solutions. Because of this, businesses are more capable of making better business and marketing decisions.
Data discovery is one of the top three business intelligence trends this year. It’s the process of discovering patterns and outliers in data to make decisions.
To do this, you need to be able to understand data relationships. New interactive and visualization types of data discovery are making this happen. The complexity of data breaks down into easy to understand models through dashboards.
This helps decision-makers spot trends and outliers in an instant. New data discovery tools democratize data. A large number of company employees are capable of revealing insights and providing suggestions.
Developers are focusing on making software that’s:
- Easy to use – You don’t need deep coding, technical, or statistical knowledge
- Agile – Users can manipulate the data to find specific answers to their questions
- Efficient – Visualization models provide valuable insight instantly
- Capable – Large volumes and varieties of data will still be presented cleanly
Artificial Intelligence is becoming more capable and sophisticated. It’s modeled off of complex human intelligence.
Instead of receiving static data reports, AI and machine learning make it possible to receive real-time reports. The reports alter depending on historical trends. Anomalies and errors are quickly eliminated based on AI learning.
Moreover, you no longer need to have an IT background to discover important insights. The manual manipulation of data is becoming less necessary.
You only have to click on a piece of data to receive automated anomalies, key segment correlations, and what-if analysis.
Predictive and Prescriptive Analytics Tools
Predictive analytics analyzes information from existing data and forecasts probabilities. Prescriptive analytics, on the other hand, takes those probability forecasts and determines what decisions should be made to reach certain goals.
Of course, the applications for these predictions are innumerable. Decision-makers can adjust pricing based on future trends. Marketers can determine customer responses and adjust their campaigns accordingly. Bankers can generate future credit scores.
This is all done through Artificial Neural Networks or ARIMA. Artificial Neural Networks mimic the human brain through complex mathematical formulas. ARIMA compares how past data has affected present data, and broadcasts that to the future.
More and more organizations are moving their data to the cloud, which has boosted the prevalence of cloud analytics. Moreover, companies are also opting for multi-cloud solutions in order to completely safeguard against the possibility of data loss.
Companies are finding that the cloud provides a host of benefits, including:
- The ability to access information anytime, anywhere.
- Implementing and deploying solutions is quicker in the cloud.
- The cloud has low overhead and easy scalability.
- The cloud gives a competitive edge through the quick access of democratized data.
Ad Hoc Reporting
To better match the specific needs of companies, end users are more capable than ever of creating on the spot reports. These reports are specific to the questions they need answered.
Ad hoc reporting is a feature that creates a more efficient method of answering common questions. It helps with day to day decisions your company needs to make.
These reports can even be automated to deliver straight to employee’s inboxes at the beginning of the day or week, greatly lessening the workload. Some industries that commonly use ad hoc reporting are:
- Retail and wholesale
It can become cumbersome to deal with large sets of data that aren’t relevant to the questions you need answered. Ad hoc reporting is a straightforward, accessible way to filter data sets for your needs.
Achieving Success through BI
As you can see, business intelligence technologies of 2019 are all about moderating the massive amount of data companies are able to acquire. Through dashboards, the cloud, and sophisticated AI, data continues to be easier to access for people who don’t have IT backgrounds.
This is important because it gives your company an edge. More eyes to analyze data means more valuable feedback on the present and future growth of your company.
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