How Can AI Transform Business Intelligence? | Top Use Cases

How Can AI Transform Business Intelligence? | Top Use Cases

From deep learning-enabled software to autonomous cars, smart robots to IoT applications, AI is deepening its claws everywhere and leaving unforgettable remarks on the world. AI-enabled technologies have specific ranks in the Gartner Hype Cycle For Emerging Technologies, which indicates that AI is unbeatable in the technology world.

However, AI business intelligence and analytics capabilities are a major attraction among businesses, as the concept improves the revenue streams and gives valuable insights. Actually, the increasing volume and complexity of data within organizations are supporting the adoption of AI to enhance enterprises.

AI and machine learning are enabling businesses to pull out valuable insights that enable businesses to forecast industry trends and user behavior. That's the reason enterprises are eager to hire AI developers to upgrade solutions. More or less, AI usage in business intelligence can bestow enterprises with billions of dollars worth of information.

Wondering how AI in business intelligence can be leveraged? Let's understand the undeniable potential of AI in business intelligence.

How Can AI Empower Business Intelligence Applications? 

Business intelligence is all about processes designed to collect, process, and analyze big data. For this, enterprises leverage a variety of business intelligence tools such as Tableau, Datapine, Zoho Analytics, and more.

In this process, some issues can hamper the value the system contributes to businesses. For example, a huge volume of data can raise a capacity limit that needs to be pushed away.

Let's see how AI can solve shortcomings.

• AI Boosts BI functionality

Business intelligence's real potential can be gauged in breaking down a large volume of data into granular insights. It enables enterprises to comprehend smaller aspects of the big picture. AI boosts the capacity and functionality of BI applications too. However, the real issue can arise in real-time insight.

Actually, BI's mainstream process is to process and visualize data. But! BI can not generate this data result and predict trends in real-time. AI with the combination of latest technologies like ML infuses the capacity of generating real-time insights and trends.

Boosting BI functionality improves the value to the organization.

• Mend The Gap 

AI-enabled BI is a boon to businesses as it develops critical insight into data that businesses are not able to examine before. AI-powered BI applications process the fresh data and identify trends useful to organizations.

The usage of the latest technologies such as machine learning, natural language processing, and predictive analytics provide useful insights. For organizations, only visualized data isn't enough to see the trends, they need tools that can bridge the gap, and AI can do that.

• Eradicate Talent Storage Problems 

Business intelligence provides data findings in a visual format by processing data coming from a number of sources. However, data representation can be hard to read, even in a visual format. However, AI can define and scale information at the easiest scale and enable businesses to gain actionable insights.

Moreover, issues of talent can also debar the processes. A number of AI development companies are deploying the tech in BI to solve these problems. With AI, the right software processing can be used to eliminate some issues formed by a talent shortage; delegating tasks to data analysts can also be done easily.

• Simplifying Complex Processes 

Even with the BI solution, surveying data is a complex process. A professional data analyst has to survey more than 100s of charts to gain actionable insights. Though, AI can simplify this process using deep learning, machine learning, and NLP.

Besides, closing the gap between human and machine communication using these technologies can also help in solving this issue. AI technology with machine learning enables machines to understand human language, which can help data analytics to find connections and insights easier.

Besides, AI-enabled BI enables businesses to handle and process a large set of data, both structured and unstructured.

From above, you would have understood how AI could benefit business intelligence. Now, let's take a glance at some live use cases.

Examples Of AI In Business Intelligence 

The major AI benefits in business intelligence can be seen in HANA- SAP's cloud platform that enables you to manage databases of collected information. The solution ingests and replicates the data from a variety of sources such as apps, databases, and more.

Users can access the platform via both on-premise servers and the cloud. HANA is potential enough to include information from financial transactions, equipment, sensors, and desktops. Suppose your company staff uses a smartphone or tablet to record purchases; then, they can leverage HANA to identify trends and irregularities.

Domo isn't a very big SAP machine learning project for the business. However, Domo is expanding its reach at a faster pace. Being a business management software company, it has raised more than $500 million in funding and has developed a dashboard that collects data to aid companies in making actionable decisions.

This cloud-based dashboard can scale the size of the company easily. So, both small and large enterprises can leverage the system easily. There are 400+ native software connectors that enable Domo to collect data from a third-party application that can be leveraged to table insight and context.

Companies using Domo can pull data from Salesforce square, Shopify, Facebook, and a number of other applications to gain valuable insights on customers, products, and sales. For example, merchants can extract data from their eCommerce platform and manage software.

This information is extracted in real-time, such as in product performance.

Machine learning can be used in numerous ways to improve the application. Apptus developed by an innovation-driven AI development company,  allows businesses to find recommendations on actions they can take to improve their sales channels. Apptus is said to be a specialized software that can help businesses to connect with customer's intent and buying habits to improve revenue for the company.

Apptus has an eSales solution designed in a way that it can automate merchandising by using the predictive understanding of consumers. The software combines machine learning and big data to determine which products can appeal to consumers so companies can alter searches and provide better recommendations.

Avanade is a program jointly initiated by Accenture and Microsoft that is based on Cortana Intelligence Suite and many other solutions for predictive analytics and uncovering data-based insights.

The platform helps companies to gain more perspective and insight into the business. You can learn about consumer behavior through analytics.

Wrapping Up 

Business intelligence applications can turn out a tremendous asset to enterprises enabling them to understand big data. Though the needs of organizations would evolve with time, an AI can then spill its magic.

As businesses would need to process and present data into visual findings, and software that can make exact trend predictions in real-time would be of major significance. The AI can show its real potential there and enable businesses to seek a breakthrough in the market.

To know how you can implement the technology within your enterprise ecosystem, you can connect with Business Intelligence Consultants with expertise in tech modern integration and AI capabilities.

Author BIO

Sophia Tondon is a technical writer who graduated from Oxford University and currently working at Valuecoders.  She is having 5+ years of experience in the field of content writing.

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