mindtalks artificial intelligence: Six Business Intelligence and Analytics Trends Companies Should Follow – GISuser.com – picked by mindtalks

The pandemic changed the trends in consumer behavior and brought about significant changes in every business. The work-from-home and social distancing policies emerged, and people had to connect through technology.

In such times, business analytics plays a key role. Business intelligence facilitates the analytics teams to interpret data, extract information, and analyze trends. The right to self-service analytics played a major role in bringing about this change. In addition, the use of business intelligence is increasing so that work efficiency and quality can improve. With the emerging trends and demands, this article aims to discuss different business intelligence and analytics trends that companies should follow in the present times.

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  1. Artificial Intelligence

Artificial intelligence is used to solve complex tasks and perform complex activities by the machine with human-like reasoning abilities. The revolution of AI promises to bring about drastic changes. With the increasing complexity and volume of data that business analytics have to deal with, AI is becoming a reasonable option to aid the process. The commercial usage of artificial intelligence is helping companies extract information and insight from big data. The responsibility of the AI is to identify patterns and extract data. At the same time, the company’s analytics team presents them in the actionable form to the company.

The role of AI expands beyond that. It helps identify what is happening at every moment and recognizes and alerts whenever there is something wrong. Their ability to detect anomalies makes them an asset in contrast to standard detection methods. It allows the companies to take notice of every unexpected event immediately.

2. Predictive Analytics Tools

Predictive analytics is the most discussed business analytics trend among BI professionals. It is the exercise of extracting information from existing data to forecast the future. The predictive analytics tool helps the company solve several problems and presents new opportunities to expand the business. It helps in detecting fraud as different analytics methods combine to detect the pattern of criminal activities. With the growing concern of cybersecurity issues in business, a high-performing predictive analytics tool can help spot any abnormalities that threaten the system.

Predictive analytics tools also help in determining shopping trends, purchases, and responses. They allow the company to counter-sell their products and recommend other products to the customer they can be interested in. Hence, these tools help the business grow by attracting profitable clients to the company.

These tools also help the company forecast its resources and manage its inventory. Using this tool allows them to prepare for a customer response so that they don’t fall short. It helps in increasing the revenue and enables the company to function more efficiently.

3. Data Automation

Data automation plays a significant role in increasing the quality, efficiency, and speed of data analytics. Difficult and time-consuming tasks that create time lags and barriers in the analysis have become the responsibility of smart computing. Because of data automation, data scientists don’t have to spend a considerable amount of time to make sense of the big data. Hence, it saves the company a lot of money and reduces the operation time considerably. When you consider the cost-benefit of using data automation, you will realize that the efficiency and effectiveness of using data automation surpass the costs. With data automation in play, the data analytics team can make decisions according to the information available and preparing strategies.

4. Data Integration

You can lose or gain a competitive edge in the market simply because your data analytics team differentiates or makes sense of the big data. Analyzing big data is the key for recognizing hidden insights to the market, which your company can use to stay ahead of the competitors. The key to identifying these opportunities is through data integration in all the corresponding departments. It allows each department to understand the interconnected view of the organization. There is more need than ever to optimize and analyze big data immediately. Data integration systems help quickly analyze customer purchase behavior and manage the data sets designated for the company’s finances.

5. Mobile Business Intelligence

Mobile business intelligence is the system that allows the user to observe history as well as the real-time information needed for data analytics on smart devices. The most significant benefit of using mobile BI is that it allows the user to access real-time data and analysis at any time. They can remotely work from any different location and access information whenever needed. It creates a real-time experience that helps in increasing analytics efficiency in day-to-day operations. It allows the data scientists and the analytics team to reach quickly whenever the need arises.

Having mobile BI helps speed up the organization’s decision-making by reducing the total time spent searching and extracting information. Hence, the focus falls upon making quick decisions and making the operations even more efficient to optimize the departmental collaboration.

6. Saas Business Intelligence

SaaS BI is generally a cloud-based business distribution and intelligence model. It allows the third party to host different business intelligence tools in a safe environment. SaaS Bi tools are used in business analytics to deliver different tools and services to the company. As large amounts of data flow in every day, companies are responsible for tracking them and analyzing them to find out the key performance drivers of the business. Data analysis on big data also shows the financial aspects of the business. Data analytics use SaaS tools to conduct a comprehensive and extensive data analysis on the cloud. It allows them to access every data source on the cloud dashboards through their remote working devices. It will enable the workforce flexibility of working from remote areas. As the provider, you will have the control to allow any party access at any time from any place.

Conclusion

Data analytics is the biggest concern in the rising trends of real-time data and big data. Moreover, with the changing consumerism trends, the need for data analysis increases. Hence, companies use every tool available to make the process more efficient, quicker, and more manageable. The tools we mention in this list are ideal for decreasing operational costs and increasing efficiency. Apart from that, some of the tools allow the data analysts and corresponding team members to work remotely and access data at any time. It is a huge benefit in the growing trends of remote working due to the pandemic situation of the world.

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