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Five Major Business Intelligence Trends to Watch out for in 2022
Business intelligence (BI) has evolved significantly in recent years and is far from superseded by artificial intelligence. Indeed, since migrating to the cloud, applying AI and machine learning, and embedding it, it has grown more efficient and user-friendly.
Fremont, CA: Data is an asset that must be used efficiently by today's business executives to maintain efficient corporate processes. They demand robust data analysis tools to assist them in making decisions. Businesses adopt complex analytics and data science to acquire insights and make better decisions, resulting in your BI department being a profit center.
BI is a crucial tool for both small and large enterprises; it is rapidly expanding and will shape how firms interact with data in the future. As a result, it must be mobile, adaptable, and user-friendly.
Here are five significant themes that will affect the future of business intelligence:
Cloud services are the most popular trend in business intelligence, especially with the widespread use of remote working. Cloud-based BI allows apps and data to be accessible from anywhere and at any time. In addition, Software-as-a-Service (SaaS) programs are growing increasingly popular because they can be accessed through any web browser, allowing insights, data, and answers to be accessed anytime, from any location, and on any device.
However, data quality remains one of the most difficult challenges for data analysts. Good data quality is crucial when attempting to acquire correct insights from accessible data to make the best business decisions. Businesses understand the enormous financial consequences of making choices based on poor data quality; thus, they create a Data Quality Management (DQM) program to ensure efficient data analysis.
Automation is Key:
RPA automates everyday activities that formerly required human intervention, and it provides a quick and dependable technique of retrieving data from diverse systems. It then does preliminary quality checks on the data and combines it into a single file or report ready for analysis. As a result, RPA can increase productivity and efficiency in most enterprises.
Collaborative BI, also known as Social BI, combines traditional business intelligence with collaboration tools such as social media and online technology. It enables more accessible report sharing and improved involvement between stakeholders and subject matter experts to make better business decisions. Collaborative BI, which is geared at enhanced problem-solving, enables the exchange of business ideas or problem solutions via Web 2.0 platforms such as Wiki and blogging
Empowering technologies like AI and machine learning to aid with data preparation, insight production, and insight explanation to augment how people explore and analyze data in analytics and BI systems. It also helps expert and citizen data scientists by automating many parts of data science, machine learning, and artificial intelligence model development, management, and deployment.