Real Time Examples of Artificial Intelligence Incorporated with Business Intelligence

Real Time Examples of Artificial Intelligence Incorporated with Business Intelligence

Modern day enterprises seem to enter into a new data-driven era. One was science fiction is now made possible with the help of advanced technologies like machine learning, artificial intelligence, and internet of things, etc. Companies largely use machine learning algorithms now to identify the trends and derive actionable insights in a wide range of industries with vast reams of data to make quicker decisions and position them to be highly competitive in real-time.

This is not a very simple process for organizations to incorporate machine learning and artificial intelligence into their business intelligence applications. However, there are many who are consistently experimenting with the same. AI helps organize the data collections and test the algorithms with data to check for accuracy over a few months and see where the business gets stuck.

However, as AI is gaining momentum, many prominent application providers have gone far beyond creating the traditional software to develop more holistic platforms, which can automate the business intelligence and analytics processes better. Some of the major vendors, including SAP, General Electric, Siemens, etc., now offer custom software suites. Also, there is an emerging number of providers in the startup market playing with AI in business intelligence. In this article, we will try to provide some real-time examples of the leading AI platforms.

SAP –Artificial Intelligence for Turning Databases

SAP is offering HANA, which is a platform for organizations to manage the DB info collected. In short, it helps to replicate and ingest structured data like customer info, sales transactions, relational DBs, app data, and other data sources. HANA can be installed on the cloud or as an on-premises installation. This platform can also take the information gathered from various access points across the businesses, including desktop computers and mobile platforms. Data can be done from sensors, financial transactions, and various production and industrial equipment. Suppose your sales staff uses the company’s smartphones or tablets to record or purchase the orders. In that case, the data from such transactions can also be analyzed using HANA to understand the trends and irregularities.

A classic user of HANA is Walmart, which uses it to process huge volumes of their transaction records in a matter of seconds. Walmart now operates about 11,000 stores, and so you can imagine the volume of transactions they undertake. Considering this example, machine learning can be used to call attention to many variances. For example, suppose an application is installed on the factory manager’s computer or smartphone to monitor an equipment’s function. In that case, any data related to a production slowdown can be gathered in real-time to administer the best course of action when needed. For AI-related database solutions, explore what can offer.

DOMO – Artificial Intelligence for Business Dashboards

Not only have the big players liked SAP who develop ML platforms for businesses. However, Domo is a smaller one, which is growing at a faster pace now with its business management suite and raised nearly $500 million in funds. They are offering a business dashboard that gathers information to help organizations quickly and insightfully make decisions. This cloud-based system can scale up or down based on the organization’s size, and it can also be used collaboratively by teams of 50 or larger. There are about 400 native software connectors that let DOMO integrate with various third-party apps, and it can also be used to offer some insight to give a proper context to BI.

This lets the companies use DOMO as a customized way to pull data from various platforms like Square, Salesforce, Shopify, Facebook, and various other applications, which they used to gain insight into their sales, customers, or product inventory. For example, Domo users who are merchants can also extract data from the Shopify POS e-com software, which can be used to manage their online stores. This information can further be used to generate some quick review reports and identify the market trends in real-time like product performance etc.

Apptus – Artificial Intelligence for Sales Enablement

There are many ways through which machine learning can help enhance business applications. Apptus is one such solution which offers recommendations to business on taking acts to boost the sales operations. Apptus specializes in establishing a connection between the intent of the customers to buy an entity and the business’ realization of the revenue.

Apptus’solution of eSales is custom-designed to automate the merchandising based on the predictive understanding of the consumers. This software helps to combine machine learning with big data to determine which all products may appeal to the customers as they search for recommendations online.

In standard use of Apptus, while the customer visits an online store using the eSales platform of Apptus and looks for a product, the integrated machine learning solutions will exact the product and display all related phrases. It can also automatically display the products associated with the related phrases along with the search terms.

Now, many companies use Apptus like, a bookseller business from Sweden, who use this platform to minimize their overhead by tapping into the automated technology. 

Avanade – Business Insights with AI

Came up as a joint venture of Microsoft and Accenture, Avanade leverages the capabilities of Cortana Intelligence Suite to do predictive analysis. Businesses like Pacific Specialty tap the benefits of Avanade with an intention to give a better perspective and insights to the staff. The goal of Avanade is to use the policy and customer data to help the sales team drive in more results. By understanding the exact behavior of the policyholder and the market trends through analytics, Avanade can advise the scope of development of new products accurately.

Along with these, you can see many more examples of AI in business intelligence like BI and AI applications for heavy industries like General Electric, Predix for logistics management, Aircraft Landing Gear Prognostics offered by GE and Infosys, Siemens – AI to Monitor machine fleets, etc. By considering your area of focus in business intelligence, you may find AI to deliver value.