The Benefits and Challenges of Big Data Analytics for Businesses

The Master of Science in Information Systems with a concentration in Business Analytics online program from Murray State University prepares graduates to become business and technology leaders who can address organizational problems by applying big data. Courses focus on data sourcing, organization and management, as well as data-driven decision-making and statistical modeling using modern business analytics (BA) tools. Course professors are experienced leaders in the field who are versed in project management methodologies and industry tools, and they are highly committed to developing the next generation of big data leaders.

Benefits of Big Data

According to software developer SAS Institute, “Big data analytics examines large amounts of data to uncover hidden patterns, correlations and other insights. With today’s technology, it’s possible to analyze your data and get answers from it almost immediately — an effort that’s slower and less efficient with more traditional business intelligence solutions.”

Using big data have a number of benefits, including:

  • Improved operational efficiency
  • Risk assessment and mitigation
  • Production optimization
  • Cost savings
  • Smarter product and service development
  • Improved customer experience
  • Optimized pricing for revenue and profit
  • Better credit risk models
  • Fraud spotting and reduction
  • Increased customer and employee retention
  • Increased opportunity for innovation
  • Easier regulatory compliance

Business intelligence (BI) is the methods and tools used to collect and organize raw data in order to contextualize, analyze and derive insights for smart decision-making. The volume of collected data is enormous, with so many company functions generating datasets from diverse sources and in myriad forms.

Indeed, the volume is so massive that the industry in the U.S. is projected to be worth $247 billion in 2022. The IDC predicts the world’s collected data will surge to 175 zettabytes by 2025 — enough to fill stacked Blu-Ray discs to reach the moon 23 times.

Challenges of Big Data

For individual businesses, the challenges in compiling and successfully applying big data are as follows:

  1. Organizing and processing data: Amassing unstructured data is easy, and because of data’s exponential growth, many companies are stuck somewhere between compiling and processing. Batch processing takes the next step by examining data blocks over time, and stream processing evaluates small batches at once for quick decision-making. The latter is a more complex stage.
  2. Cleaning and maintaining quality data: Disorganized, duplicate, irrelevant and improperly formatted data can lead to flawed insights and poor decisions. Therefore, expertise in data cleaning is essential to moving forward with analytics.
  3. Analyzing data: The process of turning raw data into meaningful and actionable insights requires data mining to identify patterns and relationships; predictive analytics to forecast the future and identify risks and opportunities; and deep learning with artificial intelligence (AI) and machine learning (ML) to extract more meaningful patterns.
  4. Making data accessible: Most data users in an organization need tools and platforms to see and understand data, including enterprise resource planning software that centralizes and automates the distribution of data and software with visualization dashboards. These graphic representations provide context for data, from which analysts can draw insights. Depending on the business function or department, different data users will focus on unique key performance indicators (KPIs) or metrics that measure actionable data and pinpoint key business trends.

Examples of Big Data in Use in Telecom

The telecom industry provides several examples of how the application of big data has helped to solve challenges. With big data tools, telecom professionals can do the following:

  1. Optimize capacity: Network usage analytics enable companies to reroute bandwidth, develop more innovative infrastructures and design new services to meet consumer demands.
  2. Monitor and prevent customer churn: Analytics provide the tools for companies to know when customers are at risk for turning to competitors. Analysts have developed successful time series and relational models that predict when customers may potentially leave so the business can act before it is too late.
  3. Develop new product and service offerings: Telecom companies have segmented their customer bases and identified specific use matters and behaviors to map certain features and benefits. This process has enabled them to develop more attractive offerings to customers with unique needs.

The program’s curriculum includes two core courses in this industry. Telecommunication Principles presents the problems and solutions involved in communicating over extended distances. Topics include fundamental physical and electronic concepts, information theory, types of media, requirements and capacity calculations, modulation and multiplexing methods, standards and architectures, modern applications and issues. Telecommunication Project Management presents the competencies to implement project management processes established by the Project Management Institute Body of Knowledge (PMBOK).

Designed to Advance Your Career in Analytics

With courses in data management, enterprise resource planning and computer information systems, the Murray State University advanced online program in information systems provides graduates with the skills to use big data in any number of roles to solve their employers’ greatest challenges.

Learn more about Murray State University’s online Master of Science in Information Systems with a concentration in Business Analytics program.

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