The Importance of Big Data

In today’s complex business world, interpreting data is more important than ever. Experts often use the term “big data” to refer to the power that data holds, and its potential to influence organizational strategy and decisions. This term summarizes how technological advances have vastly increased the amount of data, the sources it comes from, and how quickly it can be collected. If you’re new to the space, however, you might be asking yourself, “Why is big data important?”

The answer is that big data analytics and data mining allow companies to make smarter strategic decisions and outflank the competition. In this respect, the importance of data analytics is unquestioned — companies have used primitive data analytics tools to gain insights into their businesses for centuries. What’s new in the last decade is that the vast increase in data requires businesses to use more complex analytical methods than those they used in the past. This increase is not just a reference to the amount of data being created, but also of its sources and the velocity with which it can be captured. As a result, companies have developed new data analytics tools, often powered by AI or machine learning algorithms.

For instance, consumer goods companies might employ a “social media listening tool,” which allows them to sift through the trove of data created by social media users, and monitor what people are saying about their brand. Another example many of us are familiar with is how streaming services, such as Netflix and Hulu, employ smart recommendation algorithms that analyze a consumer’s viewing history to recommend new content tailored to them.

A graphic that explains what a social media listening tool does.

But these are just a few of the many applications of big data. In this article, we’ll offer a more in-depth explanation of what big data is, the importance of big data, the benefits it can offer businesses, and how it’s being used in various industries today.

Benefits of Big Data Use

Big data analytics allows a company to obtain a more complex, knowledgeable understanding of their business. This analysis usually comes from data scientists and analysts who work with different kinds of data sets, including structured and unstructured data. Structured data has already been put into a predefined format, while unstructured data is typically an amalgamation of different kinds of data formats.

Naturally, the new data-collection technologies that have accompanied the rise of the internet have led to a huge increase in unstructured data. Big data analysis tools allow these unstructured sets to be processed and turned into actionable business insights. Companies use big data analytics tools to perform all kinds of functions, from creating better customer profiles to micro-tailoring their product strategy; this allows them to save money, time, and energy, as well as remain at the top of their industry.

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Who Uses Big Data?

You might be asking yourself, Who uses big data? Are there specific industries where it’s employed? The answer is that, in today’s world, companies in almost every industry are looking to take advantage of big data technologies. Of course, the uses of big data vary widely by industry. In this next section, we’ll go over how big data applies to healthcare, business, marketing, education, and cybersecurity, to help you gain an understanding of various big data uses and how data could apply to your industry.

Additionally, if you’re thinking of pursuing a career in data science, then the following examples should give you some food for thought.

Healthcare companies and organizations are pioneering some of the most exciting big data applications, which can help us live healthier, more productive lives. You’ve probably heard of smart medical devices, which allow doctors to remotely monitor patients’ conditions. These devices are a good example of the increase in the “velocity” of data — doctors can gather data much more quickly than before and thus make faster, more informed decisions about patient care. For example, the device might detect the warning signs of a stroke before the patient even begins feeling symptoms. The doctor can then take preventative measures to prevent the deadly outcome.

Another fascinating application of big data analytics in the healthcare space is the use of machine learning models to analyze mammograms and assess a patient’s chances of developing breast cancer. Since cancer is much more treatable when detected early, these machine learning tools have the potential to revolutionize our fight against the disease.

These two examples by no means exhaust the possibility of big data in healthcare. Medical records, surgical records, behavioral data, staffing schedules, insurance information — all of these data sources can help healthcare organizations manage their patients and make better strategic decisions.

The importance of big data in business, as well as data mining techniques, is almost impossible to overstate. Statista projects that by 2025 the global big data analytics markets will reach $68.09 billion in revenue. This figure indicates just how important big data analytics will be to the companies of tomorrow.

Businesses are currently working to implement big data analytics into almost all their functions. However, one use of big data analytics that companies emphasize is the automation of decision-making functions; this involves building machine learning algorithms that can handle responsibilities traditionally handled by employees. For example, algorithms can analyze customer data to determine under what circumstances shoppers may request and receive refunds. In the future, refund decisions can then be made by a robot algorithm rather than by employees, saving time and resources.

Another area that big data analytics have a major impact is supply chain management. Algorithms can use past data along with predictive technology to provide supply chain managers with guides on how they should manage their inventory, improving efficiency and ensuring that the right items remain in stock.

All in all, we can expect that almost all fields will implement big data analysis in the coming years.

Today, thanks to the rise of internet technologies that track consumer behavior, companies have more raw data on their consumers than ever before, including their age, location, race/ethnicity, income level, and when and how they buy products. Naturally, this knowledge of customers has driven the innovative use of big data in one business area in particular: marketing.

One important way big data helps marketers is through brand positioning. How does your brand fit into your industry’s landscape? How do consumers see your brand? These are questions every marketer needs to ask themselves, and big data analytics can help them formulate the appropriate answers. Algorithms can use big data collections to refine brand positioning elements, such as pricing and finding the right targeted audience.

Additionally, companies use algorithms to manage their data on individual consumers to tailor their ads and suggestions individually. It’s unlikely that two Amazon users’ home pages recommend the same exact products, because Amazon is creating micro-personal recommendations for each of its customers. Customers love this personalization, and it’s one of the main factors that drives Amazon’s success.

Big data is also revolutionizing the education sector. For example, school administrators can use big data analytics to analyze macro-trends, such as enrollment, attrition rates, student preferences, and the effectiveness of different learning environments, such as in-person learning and online classes; this will allow them to ensure they’re offering services to students that are both effective and match student needs.

However, these large-scale applications are not the only uses of big data in education. Individual instructors can also use big data tools to analyze their own teaching methods, see what’s working for students, and develop personalized curricula.

As higher education in particular becomes more expensive, it’s important that administrators and professors keep up with student expectations and technological innovations. Using big data analytics tools can help them ensure that they’re staying on the cutting edge of higher education. Ultimately, the schools that embrace big data analytics will be the ones delivering the best student outcomes and achieving higher student satisfaction levels.

A cybersecurity attack is one of the most dangerous threats to modern-day corporations. If a company’s systems become hacked, it can be devastating to their operations and brand reputation. Furthermore, as the number and kinds of digital devices explode with the rise of the Internet of Things (IoT), the amount of vulnerable points is only increasing. As a result, cybersecurity professionals are increasingly turning to big data analytics to help create robust defense systems.

Algorithms can analyze a network’s historical data to determine a baseline for secure operations and then monitor the network for any potential deviations from that baseline. These algorithms, typically called intrusion detection systems (IDS) can track and assess these threats in real-time, alerting employees to any potential dangers. Unlike human employees, these algorithms can stay awake and alert 24 hours a day, 365 days a year, ensuring that networks are always secure.

As the IoT continues to proliferate, you should expect big data analytics to take on an even more prominent role in cybersecurity.

An image that lists out five industries that use big data.

Big Data Analytics Jobs

Given big data’s continual rise in prominence, there’s a good chance that you may want to consider a career in this space. The first step will be to acquire the skills necessary to obtain an entry-level position. You have a few options on this front, including a traditional degree, a boot camp, or pursuing self-study through textbooks or online courses.

Consider whether you want to pursue a career as a data analyst or a data scientist. As a data analyst, you will focus on using existing data sets to solve business problems — a good option for people who believe in their analytical abilities and problem-solving skills. On the other hand, as a data scientist, your objective will be to create machine learning algorithms that process large data sets. This path will be attractive if you are enthusiastic about learning more about coding and computer science.

Both paths offer opportunities for advancement and eventual progression to director positions in which you’ll take on a more managerial role. Additionally, there are job opportunities in numerous industries. While demand is particularly high in tech and finance, other sectors, such as retail, agriculture, and health care, are also in need of data scientists and analysts. Ultimately, if you’re thinking about where to start your career or changing career paths, consider the big data analytics space.

Learn More About Big Data Today

As discussed above, there are many routes to learning about big data. With the importance of data analytics on the rise, you might consider attending a data science and analytics boot camp, like Georgia Tech Data Science and Analytics Boot Camp. This 24-week online course offers a data science and analytics curriculum that will provide you with the specialized skills you need to succeed as a data scientist or data analyst, including Python, HTML/CSS, fundamental statistics, machine learning, and more.

As the importance of big data only increases, corporations will need data scientists and analysts to retain their competitive edge and dominate the market in this fast-moving business environment. Attending Georgia Tech Data Science and Analytics Boot Camp is a great way to gain a foundation in these skills and launch a lucrative career.

Importance of Big Data FAQs

If you’re unfamiliar with the big data space, you may be asking yourself, “what is big data analytics?” The answer is that big data analytics uses tools to investigate extremely large data sets to identify patterns and derive business insights to develop strategy and improve decision-making.

Data analytics helps firms stay on the cutting edge of their business and industry. Without data analytics, most companies would be flying blind when they develop their marketing and sales strategy or manage their inventory and supply chain. If a firm isn’t keeping pace with its competitors in terms of data analytics tools, it may fall behind and even face bankruptcy.

Big data sees use in all kinds of business functions and industries. While healthcare, finance, and tech companies are currently leading the charge in terms of implementing big data analytics, most industries are finding ways to employ data scientists and analysts to enhance their strategies and outcomes.

Big data and the need for big data analysis comes from the vast increase in the amount of data, its sources, and how quickly it can be collected; this is driven by the profusion of data-collection technologies, from smart devices to social media websites, that have accompanied the rise of the internet.

The great advantage of big data is that it allows businesses to glean in-depth insights about their business and industry. However, this also comes at a price, as corporations need to invest time and resources in developing this competency.

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