What is Big Data?

Big data has become an increasingly important asset for companies across industries, around the world. With the explosion of digital data, organizations are now able to collect, process, and analyze vast amounts of information to gain valuable insights and drive decision-making. This has led to a growing demand for data scientists and other professionals with expertise in data analytics, as they’re well-equipped to help organizations capitalize on the opportunities presented by big data.

Understanding what big data is and how to leverage it is the first step. Read on to explore what is meant by the phrase “big data,” how and why we use it, and why, in a world of big data, privacy protection is essential.

“Big data” is a term used to describe the large, complex, and diverse data sets that are generated by businesses and organizations in the digital age. These data sets can be structured, semi-structured, or unstructured, and are often so large and complex that traditional data processing software and techniques are not able to process or analyze them effectively.

To manage and analyze big data effectively, organizations often use specialized technologies and techniques, such as distributed computing, data mining, machine learning, and predictive analytics. These resources allow organizations to uncover insights and patterns in their data, and to make data-driven decisions that can help improve their operations and performance.

Organizations and businesses collect data from a wide range of sources, hoping to understand their customers, markets, and operations better. In our digital age, big data can come from social media, transactional systems, sensors, blogs, and mobile devices. Data collection often takes place in real time, and all the data can be stored and processed in a distributed computing environment, such as a cloud-based platform.

By analyzing large data sets, businesses and organizations can identify trends, patterns, and relationships that would otherwise be hidden in smaller data sets. This can help them make better business predictions and data-driven decisions, improve their products and services, and ultimately increase their competitive advantage in the marketplace.

Big data is useful for market research, customer analytics, risk management, and fraud detection, among other purposes. Careful data analysis can yield insights into customer behavior, market trends, and other aspects of a company's operations. Equipped with these big data insights, company leaders can make better decisions and improve performance.

Some of the key challenges associated with big data include these needs:¹

• Specialized tools and expertise to manage data and conduct thorough data analysis
• Prompt, efficient storage and processing of large volumes of data
• Data protection, including secure, private data storage

Overcoming these hurdles is essential to realizing the full potential of big data.

Big data can revolutionize the way organizations operate and make decisions. It can lead to numerous benefits, including these:

By collecting data and analyzing large data sets, company leaders can uncover trends and patterns that can inform their decision-making processes. This can help them make more informed and strategic decisions, leading to improved performance.

Big data can help organizations understand their customers and—more importantly—what their customers need and want. By analyzing customer data, they can identify trends and preferences, and use that information to tailor their products and services to meet customer needs more effectively, improving the overall customer experience.

Companies can use big data to identify inefficiencies and bottlenecks in their operations. Data analysis can help them recognize areas where they can improve processes and eliminate waste, leading to increased efficiency and productivity.

Similarly, companies can use big data to identify, understand, manage, and mitigate risks. This reduces the likelihood of negative business outcomes and helps to protect each organization's bottom line.

Privacy concerns are crucial when it comes to big data, as large, complex data sets can contain sensitive information—such as individuals' Social Security numbers, health records, and credit card details. In instances of data leaks and data breaches, malefactors can use this confidential data to cause direct harm through privacy invasion, discrimination, identity and property theft, destruction of credit ratings, and other life-altering forms of aggression.

To address this, a number of data protection laws and privacy regulations strive to ensure that sensitive data is collected, used, and shared responsibly. They often require organizations to obtain consent from individuals before collecting their personal information and to implement appropriate security measures to protect collected data from unauthorized access or disclosure.

In addition to legal requirements for data protection measures, ethics are an essential factor in collecting and using big data. For example, organizations may need to consider whether the benefits of using big data outweigh any potential negative consequences. Furthermore, they have a responsibility to be transparent about how they collect, use, and share personal information. This includes using clear, up-front communication about data collection practices, and providing individuals with the ability to opt out of data collection or request that their personal information be deleted.

Overall, privacy matters because it’s a fundamental human right, and because the misuse of personal information can have serious consequences for individuals and society as a whole. By respecting and protecting privacy, organizations can help ensure that the benefits of big data are realized without compromising the rights and freedoms of individuals.

To be certain that big data is collected, used, and shared responsibly and ethically, organizations must implement and abide by effective data governance practices. This involves ensuring that the data is accurate, complete, and up to date, and that it’s used in a way that’s consistent with the given organization's goals and objectives. It may require implementing data quality controls, training employees on data privacy and security best practices, and regularly reviewing and updating data protection policies and procedures.

It also typically calls for the creation of a governance structure, such as a board or committee, to provide oversight and guidance on data-related issues. This structure can be responsible for setting data policies, ensuring that data is used ethically and responsibly, and monitoring compliance with data governance standards.

Effective data governance also involves establishing clear roles and responsibilities for data management within the organization. This may include hiring specialists such as a data steward, who ensures data accuracy and completeness, or a data governance manager,² who oversees the implementation of data governance policies and procedures.

Develop the expertise to analyze, manage, and protect big data. Designed and created by Silicon Valley leaders, the cutting-edge curriculum of SCU’s Online Master of Science in Business Analytics (MSBA) program delves into data mining, predictive modeling, and data visualization, and provides hands-on experience using industry-leading tools and techniques.

With a global market of $273.4 billion for big data by 2026,³ the demand for expertise—and the potential for highly rewarding success—is staggering. Make sure you’re at the leading edge of a rapidly growing field. To start your career ascent, reach out to our Admissions Advisors today.