What Is Big Data Analytics? Definition, Benefits, and More | Coursera

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Big data analytics is behind some of the most significant industry advancements in the world today, including in health care, government, and finance. Learn more about working with big data and common tools to get started.
Big data analytics is a form of advanced analytics that involves collecting and analyzing vast amounts of data to uncover insights that inform decision-making.
Big data analytics tools, such as Apache Hadoop and predictive analytics software, help analysts with various steps of the big data analytics process.
Big data analytics is a practice that uses advanced techniques and technologies, such as business intelligence systems, to analyze both structured and unstructured data, helping companies understand their operations and identify solutions.
You can see examples of big data analytics in the health care industry, where health care providers have to manage information such as patient records, prescription information, and insurance plans. Learn more about big data analytics and how you can use it to help you make informed decisions. If you’re ready to get your start, earn a Google Data Analytics Professional Certificate, where you will have the opportunity to learn in-demand skills such as data cleansing, data visualization, file management, spreadsheet software, and more.
Big data analytics is the process of collecting, examining, and analyzing large amounts of data to discover market trends, insights, and patterns that can help companies make better business decisions. This information is available quickly and efficiently so that companies can be agile in crafting plans to maintain their competitive advantage.
Big data analytics uses advanced analytics on large collections of both structured and unstructured data to produce valuable insights for businesses. It is used widely across industries such as health care, education, insurance, artificial intelligence, retail, and manufacturing to understand what’s working and what’s not and to improve processes, systems, and profitability.
Technologies such as business intelligence (BI) tools and systems help organizations take unstructured and structured data from multiple sources. Users (typically employees) input queries into these tools to understand business operations and performance. Big data analytics uses the four data analysis methods to uncover meaningful insights and derive solutions.
Big data is characterized by the five V's: volume, velocity, variety, veracity, and value. It’s complex, so making sense of all of the data in the business requires both innovative technologies and analytical skills.
Though there is no threshold that separates big data from traditional data, big data is generally considered to be “big” because it cannot be processed effectively and quickly enough by older data analysis tools.
For example, big data analytics is integral to the modern health care industry. As you can imagine, thousands of patient records, insurance plans, prescriptions, and vaccine information need to be managed. It comprises huge amounts of structured and unstructured data, which can offer important insights when analytics are applied. Big data analytics does this quickly and efficiently so that health care providers can use the information to make informed, life-saving diagnoses.
Data will become increasingly integral and transformative to day-to-day business operations, according to McKinsey & Company [2]. Big data analytics is important because it helps companies leverage their data to identify opportunities for improvement and optimization. Across different business segments, increasing efficiency leads to overall more intelligent operations, higher profits, and satisfied customers. Big data analytics helps companies reduce costs and develop better, customer-centric products and services.
Data analytics helps provide insights that improve the way our society functions. In health care, big data analytics not only keeps track of and analyzes individual records, but also plays a critical role in measuring public health outcomes on a global scale. It informs health ministries within each nation’s government on how to proceed with public and population health policy and devises solutions for mitigating future society-wide health problems.
There are quite a few advantages to incorporating big data analytics into a business or organization. These include:
Cost reduction: Big data can reduce costs in storing all of a business's data in one place. Tracking analytics also helps companies find ways to work more efficiently to cut costs wherever possible.
Product development: Developing and marketing new products, services, or brands is much easier when based on data collected from customers’ needs and wants. Big data analytics also helps businesses understand product viability and keep up with trends.
Strategic business decisions: The ability to constantly analyze data helps businesses make better and faster decisions, such as cost and supply chain optimization.
Customer experience: Data-driven algorithms help marketing efforts (targeted ads, for example) and increase customer satisfaction by delivering an enhanced customer experience.
Risk management: Businesses can identify risks by analyzing data patterns and developing solutions for managing those risks.
Entertainment: Providing a personalized recommendation of movies and music according to a customer’s individual preferences has been transformative for the entertainment industry (think Spotify and Netflix).
Education: Big data helps schools and educational technology companies alike develop new curricula while improving existing plans based on needs and demands.
Health care: Monitoring patients’ medical histories helps doctors detect and prevent diseases.
Government: Big data can be used to collect data from CCTV and traffic cameras, satellites, body cameras and sensors, emails, calls, and more to help manage the public se