Kayla Matthews

By: Kayla Matthews on July 29th, 2019

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How BI Data Strategies Are Driving the Data Center Industry

Data Center | Artificial Intelligence (AI)

Business intelligence (BI) occurs when enterprises use specialized tools to gain insights about how to run their operations. It's used to get informed of trends, changes and other notable shifts that could help them maintain profitability and avoid pitfalls. BI strategies depend on data centers, too.

BI Data Strategies Prove the Worth of Data Center Investments

Lowe's, the home improvement brand, was an early adopter of BI when it built a data center to back up some of its information in 2007. Even then, the retailer tracked 50 million items to help with inventory planning and ran nearly 170,000 reports each week.

Some businesses may not have the resources that Lowe's does, making an in-house data center unfeasible. In that case, they'd likely look for providers that have colocation services. Then, they could benefit from how data centers facilitate BI needs without such substantial upfront investment.

When well-known companies like Lowe's start depending on BI in such large-scale ways, they demonstrate to other brands that it's worthwhile to follow their lead. As such, the overall data center industry benefits once companies start seriously investigating how to use BI.

Using BI Leads to Competitive Advantages

Despite the rising popularity of BI solutions, some company executives still balk at adopting them. However, research carried out concerning companies in the United Kingdom that are using BI indicated that doing so opens new opportunities. Companies saw 24% more sales on average in 2018 compared to the companies without BI tech. Software was the most popular way that enterprises utilized BI, the survey found.

BI tools also make executives aware of information they would likely miss if they didn't have access to the technology. For example, a company might discover that an inefficient process leads to more equipment shutdowns or consistent productivity losses. Then, it could use BI software to learn the methods that could help reduce such slowdowns.

Companies know they must constantly look for ways to remain competitive in an ever-challenging environment. Data centers align with that organizational need by providing the computing power and reliability required so BI users can get the most out of their chosen software. Organizations find it's more difficult to depend on BI if they have trouble accessing the data when required. Then, what should be a competitive advantage leads to a disadvantage.

However, since data centers often provide uptime guarantees, the enterprises that depend on them for BI reasons realize they're reliable. They support the ongoing desire to remain competitive. Data center providers with savvy marketing teams could specifically call out their uptime guarantees and connect them to BI success.

Thoughtful Data Strategies Help Businesses Excel

Sometimes, companies start collecting information just because the option exists. However, if they don't figure out a data strategy first, enterprises could find that their BI investments don't have the expected payoffs. A typical data strategy includes several components, but its goal is to define how using it will empower a business.

A data strategy may include specific goals for a company to achieve, a timeline for meeting them and a discussion of what internal changes have to happen to maximize information for BI. Companies often conclude they need external assistance to capitalize on what BI offers. Then, they reach out to data center providers to talk about their needs and expectations.

When that happens, businesses and data centers both benefit from how enterprises increasingly depend on BI. As data center brands engage with prospective and current enterprise customers, they should use language that makes sense to companies. Offering case studies about how a data center has already helped an enterprise with its BI needs could also help.

Businesses Investigating Real-Time BI With Artificial Intelligence

Companies often see if artificial intelligence (AI) could give them information in real-time to streamline their operations. AI is a data-intensive technology, particularly when it responds to in-the-moment changes. Some analysts even say data is the fuel for AI.

If companies decide AI should be part of their business intelligence plans, they also need the data center power to make it happen. Often, that means seeing how providers can help.

The AI techniques companies ultimately use to learn more about their businesses may center on what happens at a recently opened Walmart test facility. The retailer says the AI monitoring system could report when spills occur in heavily trafficked areas of stores so team members can get notifications to clean them up. They could also learn when to replenish shopping carts or which items are nearly sold out. Walmart noted that 140 million shoppers in the U.S. visit its stores or website every week.

The brand has plenty of data to work with during this experiment. When other companies use BI on a large scale or implement aspects of AI, it means they'll need increased space and computing power to make this level of analysis work for them. Data centers could provide it.

Data Centers Readying for Increased Demand

Experts at JLL believe the overall data center demand will double by 2021. They cited growing cloud adoption rates and the rising consumption of online content as a couple of reasons for that change. Additionally, research from Gartner showed that 87% of businesses have low BI and analytics maturity levels. It also found that an aging IT infrastructure was one of the top causes for the immaturity. Data centers could help businesses use BI more competently.

Mutually Beneficial

This coverage highlights how companies using or considering BI benefit from data centers, and those facilities get more enterprise clients. This connection will likely continue as BI retains importance, and data centers demonstrate how they impact business growth.

 
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About Kayla Matthews

Kayla Matthews writes about data centers and big data for several industry publications, including The Data Center Journal, Data Center Frontier and insideBIGDATA. To read more posts from Kayla, you can follower her personal tech blog at ProductivityBytes.com.

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