What Types of Business Decisions Would an EIS Use AI For?

Artificial intelligence can and should be used to make business decisions in today’s world. It can reliably predict metrics such as customer churn. There are many companies offering B2B information management solutions that promise to improve company performance (to be discussed below). Companies derive all the value from their data when it is being fully utilized. So much of the data that organizations collect goes unused.

Types of data for business decisions

There are two main types of data that can be digested for business purposes: structured and unstructured.

Structured

Structured data represents all data that is present in a known format. This can be thought of as an excel spreadsheet where data can be composed of different types such as numeric or character but is contained in a grid that can be easily searched.

Since all the data is in a predefined format, there are easy ways to grab and pull that data. Some of the most common methods are relational databases, such as SQL, which sets the size of the dataset and allows joining of tables together in an optimized fashion.

Unstructured

Unstructured data on the other hand, is data that does have a structure, but just not a consistent structure. Examples of unstructured data could be:

  1. Images
  2. Email
  3. Social feeds
  4. Microsoft Office documents, spreadsheets, powerpoints
  5. Many others

Storing of unstructured data cannot be done with a traditional relational database such as SQL. Instead a non-relational database must be used such as NoSQL via MongoDB. NoSQL based solutions became popular with the introduction of the internet when applications scaled to millions of users and all of the user information that was needed had to be stored in one location. This eliminates the need for joining numerous tables together as is often done in relational databases.

As you can see, these types of unstructured data feeds contain very valuable information. Without these being fully utilized, companies will be left in the dark in entire facets of their customer population (such as social media).

Impact of utilizing unstructured data

An estimated 80% of the world’s data is unstructured according to IBM. That is why there are systems that can help manage and store this data to allow easier business decisions to be obtained. Applying artificial intelligence on the information contained inside an EIS can result in valuable business decisions.

Four examples of Enterprise Information Systems for AI

In the enterprise information space, there are some very clear frontrunners. These enterprise data management providers all create solutions for organizations looking to get more value out of their data, though each have individual strengths and weaknesses.

IBM

IBM is certainly one of the leaders in enterprise data management services. Additionally, they have a strong AI infrastructure backbone too. Once a company’s data sources are nicely integrated into an IBM cloud, the potential for AI is there too. IBM manufactures their own training servers consisting of between 2 and 6 Nvidia Tesla GPUs

Enterprise Information systems

As an example the company called Enterprise Information Services offers enterprises data management services for institutions such as the US Army. For the Army, Enterprise Information Services compiles biometric records for identification purposes. This data is likely mostly unstructured consisting of fingerprints, images, and documentation. However, application of artificial intelligence can allow them to offer real-time operations of their identification platform.

Cognizant

Another innovator in the enterprise data realm is Cognizant. They are forward thinkers in terms of utilizing all an enterprise’s available data.

SAS

A white paper by the company SAS shows how unstructured data can be tapped into for business decisions. The paper discusses the level of textual data spanning sources from emails to tweets. SAS contains a module called the SAS Text Miner that can enable all this text to be mined for the most useful insights. SAS also offers tools such as the SAS Text Import Tool and the SAS crawler that can scan through formats such as .txt, .xml, and .xls data to clean and standardize the data for further importing and analysis.

Concluding Remarks

The use of artificial intelligence on unstructured data can generate some of the most valuable business decisions. Pulling together data points gathered from email, images, and social feeds allows complete pictures to be painted for the decision makers at an organization.

Interested to read more about AI? Read about the AI category that attempts to emulate how human brain works here.

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