Students pursuing an online MBA degree want a well-rounded education in current, relevant topics that influence the economy and any specific concentration they may pursue. In an increasingly digital world, a strong grasp of key processes and systems used to manage and analyze data is crucial to be a truly connected and informed leader in a variety of different roles. The importance of data warehousing and data mining, for example, is hard to overstate. The ability to store large amounts of data in a cost-effective and secure way, as well as to review and gather useful guidance from it through automated processes, has transformed the way many modern organizations operate. This is one area where MBA students should not only understand its underlying concepts, but also how they relate and differ from each other. Additionally, it’s crucial to recognize how these processes apply to business operations.
What is a data warehouse?
A data warehouse is a single repository for information collected by a business or other organization. It allows a company to keep all relevant data in a single digital location. That data can come from several sources, such as transactional systems and a variety of individual databases. Some types of data are common across the modern economy, while others may be specific to a given industry or individual business. In practice, data warehouses should feature strong security measures to keep potentially sensitive or valuable information safe. They should also allow data scientists, analysts, and other qualified users to interact with the information as users seek to turn large amounts of information into actionable analysis and guidance.
A data warehouse, while a relatively uncomplicated concept, requires sophisticated infrastructure, knowledge, and support to establish and maintain. IT staff must regularly perform critical work relating to the data warehouse. Responsibilities may range from ensuring data continues to flow into the warehouse as intended to troubleshooting errors and ensuring storage is secure. A data warehouse is also often just one element of a much larger system supported by a number of processes. One simple structure involves the individual data sources feeding into the staging area, which leads to the data warehouse. From there, information flows into data marts, which offer data specific to an individual department, function, or other specification. Many other, more complicated models exist as well.
What is data mining?
Data mining is the automated extraction of meaning and insight from large data sets, done in a way that would otherwise be time and cost prohibitive through human analysis and more simple systems. It involves disciplines such as statistics, machine learning, and database systems. Data mining in business uses large information sources to generate actionable analysis and intelligence intended to support general or specific business practices. Some examples of the application of data mining include identifying and broadening successful marketing efforts, discovering problems and delays in common workflows, and locating potential opportunities for the business to expand or diversify. In concept, there are few limits to the areas where data mining can be applied, although there are practical limits such as the processing power of automated tools, company priorities, and other considerations.
Data mining for business analytics is a well-regarded strategy in the modern economy, as businesses rely on the objective information contained within a variety of informational sources as the basis for analysis. There can still be issues with the specific ways in which data is analyzed, both in terms of technical and human error. However, basing decisions on sound, complete data and comprehensive intelligence that stems from that data is far superior than relying on gut feelings or more basic and limited analysis.
How do data warehousing and data mining compare?
Data warehousing and data mining can be seen as complementary concepts. Data warehousing focuses on the secure, stable collection of data from disparate internal and external sources, as well as passing that information on to a next destination for analysis or other review. Data mining involves finding patterns of various significance through automated tools in an in-depth fashion that isn’t practical with less-sophisticated tools. Both involve working with operational data and information that can come from a host of other sources, but the similarities end with how each workflow transports or manipulates the data.
Generally, large companies across most industries utilize these systems in one form or another. Exceptions exist, but the dependability, versatility, and general usefulness of data mining and warehousing are well understood in the modern business climate. Career fields that are somewhat or heavily involved with the function of these two processes include data science, computer science, statistics, and information technology. Additionally, marketers, financial professionals, and many other professions lean on the analysis that stems from the handling and processing of the data.
How UAB prepares MBA students for the technology-driven modern economy
The University of Alabama at Birmingham offers an online MBA degree program that prioritizes a well-rounded education focused on today’s business climate. It includes courses such as Information Technology and Business Strategy, which delves into the role of technology in management and operational planning. Additionally, the Management Information Systems concentration offers several courses that dig deeper into the role of technology in modern business from a variety of perspectives. To learn more about what UAB has to offer prospective students considering taking the next step forward in their educational and professional development, speak with one of our academic advisors today.
Recommended Reading:
What is pay-per-click marketing?
Sources:
UAB Collat School of Business: Course Descriptions MBA
UAB Collat School of Business: Online MBA Degree Program