Key Business Intelligence Trends to Watch out for in 2020

By CIO Applications| Wednesday, September 09, 2020

Business Intelligence trends and enhancements have become essential in making decisions, and businesses are utilizing this technology to stay updated when it comes to digitization and competition

FREMONT, CA: Many organizations are implementing business intelligence (BI) insights to assist in any process they have for decision making. BI is becoming faster and more accurate about its reports, whereas analysis of data increases its strength and predicts essentials change and develops drastically.

Here are four major BI trends in 2020:

Data Governance

Because of the growing number of data sources and its complexities, the need for data management has become important. If the data is of poor quality or incorrect, the business decision's outcome can prove to be disastrous for the organization. By implementing data governance, only one specific person will have access to the data, which increases reliability for improved and accurate business decisions.

Overall Efficiency

BI in organizations has helped make better decisions, increased employee satisfaction, and finance. BI tools will also quantify marketing more and remove wrong assumptions.

Increasing AI Adoption

AI is incorporated in every organization to improve business productivity and decision making. BI tools help dissect historical data and performance, which is then used by data analytics to collect reports that managers can use to make decisions.

The advances in AI development has helped BI to move to a more dynamic approach to analytics.

Creating Actionable Insights

Small and medium businesses will not need to invest time, effort, and money in analyzing raw data with the help of augmented analytics, eliminating the need for data scientists.

Also, the unification of machine learning (ML) and natural language processing (NLP), augmented analytics-enabled devices will understand and link data on their own. AI utilizes independent detection of data system anomalies, no matter the data set. Therefore, organizations will only need to provide raw data.

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