Two business professionals in business attire looking at data on a computer screen

For as long as humanity has conducted business, we’ve used data to make better decisions. Farmers observed which crops flourished in which seasons and planted accordingly. Vendors saw which products sold the quickest at market and increased their inventory. But, as business has changed and grown over the centuries, so too has the amount — and complexity — of available data.

In a single minute of a given day, humanity produces more data on the internet than most individuals can even comprehend. With the increasing prominence of AI, that will not be slowing down anytime soon.

According to Edge Delta, the total amount of data created, captured, copied and consumed globally in 2023 was approximately 120 zettabytes. To understand that scale, one zettabyte is equal to one million petabytes, and a single petabyte is estimated to be the equivalent to 500 billion pages of standard printed text. When people say we’re in the era of Big Data, that may be a bit of an understatement.

While a single business may not be producing zettabytes of data, they still have access to vast amounts of data. To understand and leverage this data, businesses need highly skilled IT and data professionals who know how to collect, organize and harness data effectively. One way to get those skills is with a Master of Science in Information Technology from a program such as the one at the Cal Lutheran School of Management.

How Is Big Data Used in Business Decisions?

Businesses that are able to effectively analyze their data reap significant benefits, such as improved efficiency and the ability to make better strategic decisions at every point of the business cycle. One key way to better understand your organization’s data and use it for decision-making is by implementing a data analytics process.

Organizations use data analytics to predict and plan for the future

Data analytics, at its simplest, is a discipline that aggregates and simplifies data so that organizations can better understand performance. In business, this typically means leveraging large datasets and transforming the raw data into actionable insights. In the age of Big Data, analyzing these datasets often requires more brain capacity than an individual can handle, so data analysts employ a wide variety of tools to help them extract, synthesize and visualize data.

Decision-making depends on employees who understand data

Data analysts typically have a variety of technical skills, including math, statistics and programming, so that they can effectively cleanse, mine and process the data. These individuals and the processes they create allow companies to make observations, find patterns and make predictions about the future.

Four types of data analytics

There are four main types of data analytics: descriptive, diagnostic, predictive, and prescriptive analytics.

  • Descriptive analytics describes what’s happening currently, such as how many customers are purchasing a certain product.
  • Diagnostic analytics tries to answer why something is happening.
  • Predictive analytics attempts to predict what may happen in the future.
  • Prescriptive analytics is the process of identifying a recommended course of action based on the data.

How Are Companies Using Data to Make Decisions?

Coca-Cola

As the world’s largest beverage company, Coca-Cola collects incredible amounts of data across all of its operational processes, from supplier information to the “Freestyle” fountain machines that allow customers to customize beverage flavors.

Data from those fountain machines showed significant demand for Cherry Sprite. Coca-Cola listened to this data and brought Cherry Sprite to market in retail locations.

With a massive social media presence and over 100 million followers, Coke is also able to mine that data to make better business decisions. One way they use emerging data technology is by identifying posts with photos of Coca-Cola beverages. This allows the company to detect trends and target marketing to its most loyal customers.

Amazon

Retail giant Amazon uses customer data to make targeted product recommendations. They also leverage data from a number of sources to dynamically update item prices millions of times a day, based on factors such as availability, competitor pricing and how often the product is viewed.

Starwood Hotels

The Marriott hotel brand Starwood Hotels uses data to power dynamic pricing based on a number of factors, including weather, economic conditions, availability and nearby events. The updated process increased revenue by 5% per room.

Starwood Hotels has since increased their investment in data by placing Amazon Echo devices in all rooms and integrating new processes like facial recognition systems to expedite check-in.

Netflix

Netflix continues to succeed in the face of increasing competition in part by using data to personalize recommendations and make production decisions. They also use data analytics before shows even make it to the platform, as they analyze millions of user ratings and playback data to predict the popularity of new shows and films.

L’Oréal

The cosmetics company L’OrĂ©al may be more than a century old, but it uses data analytics to drive its research and development practices and its marketing approaches. For instance, L’OrĂ©al leverages data from retailers, online shopping behaviors and social media activities to predict product popularity, identify emerging beauty trends and guide product development. After a product launch, they track the customer’s journey from interest to purchase, allowing them to refine and personalize marketing campaigns accordingly.

In product development labs, they make research decisions using databases that pull in 50 million pieces of data every day, ranging from microorganism development to the effects of pollution on skin.

Uber

The ride-sharing app Uber uses data in basic functions, such as pairing riders with drivers and estimating wait times, ride times and fares. But where the company is truly using data science to make change is in their efforts to mitigate supply and demand issues. Their dynamic pricing system raises the cost of trips when ride requests spike, which keeps demand from skyrocketing out of control, but this practice is frustrating for customers.

Uber has also rolled out heat maps to help drivers navigate to the busiest areas to meet rider demand, and they are experimenting with AI tools to predict where demand might increase. For their food delivery arm, Uber Eats, they cross-reference traffic and food preparation data to keep meals as fresh as possible.

How Do You Advance Your Data Analytics Career?

If you want to improve how your company uses data, a good step is to pursue a Master of Science in Information Technology. Cal Lutheran offers an MS in Information Technology (MSIT) that covers the crucial steps of the data process: collection, management, mining, analysis and implementation. Students in the MSIT program work with expert faculty on dynamic projects, gaining skills that prepare them to make an immediate difference in their organization’s IT systems.

The graduate information technology curriculum includes courses like Data Management, which introduces students to the foundational principles of collecting and organizing data and teaches how to use structured query language tools to model and aggregate data.

MSIT students have the opportunity to choose a specialty track in data analytics. Courses in this track include Data Warehousing and Business Intelligence, where students learn how to use analytical applications to extract business intelligence. They also study the distributed processing of large-scale, unstructured data using Apache Hadoop and other Big Data technologies.

Earn Your MS in Information Technology from the Cal Lutheran School of Management

Get the skills you need to stay ahead in the ever-evolving world of IT. With online and hybrid courses designed for working professionals, Cal Lutheran’s MSIT program offers the essential knowledge to stay ahead and the flexibility you need to manage other responsibilities.

The School of Management at Cal Lutheran is dedicated to producing graduates who are well prepared to succeed in their personal and professional lives — who lead, think, communicate and follow through with sustained excellence. As a Cal Lutheran School of Management student, you’ll learn from experienced faculty and benefit from personalized attention in small class sizes.

Download a program brochure or start your application to the MS in Information Technology.

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