The rate at which information is being collected around the world is unparalleled. There is a corresponding demand for skilled analysts who can make sense of the burgeoning amounts of data.

IDC predicts that by 2025, the world’s data will amount to 175 zettabytes. To put it in context, it would take 12.5 billion hard drives the size of the largest hard disc currently accessible to download all 175ZB.

More digital expansion is predicted for the future of big data, and the storage, analysis, and application of data are crucial to the success of virtually every company.

What does the Future of Big Data in Business Look Like?

The future of innovation lies in the hands of data analysts and data scientists who can sift through massive amounts of data to find useful information.

A master’s degree in business data analytics, even if earned online, could give you a leg up when looking for work in this exciting new industry.

The banking, retail, manufacturing, financial, healthcare, and government sectors are just a few of the many industries investing considerable resources into big data analytics.

Data and business analysts work in these sectors and use cutting-edge data analytics tools for improved business decision-making, trend forecasting, and business growth.

Jobs in the field of big data have a promising future. Between 2016 and 2026, the BLS projects a 13 percent increase in employment opportunities across all computer and information technology occupations in the United States.

Numerous careers involving big data are also available in this field, such as database administrator, information security analyst, network, computer systems administrator, and others. 

Here are a few Big Data Analytics trends that will shape the future of different industries in 2022:

4 Biggest Big Data Trends for 2022

1. Improved Fraud Detection in Financial Sector

Technology improvements in the banking sector over the past decade have had an impact on consumers’ banking habits.

Consumers’ relationship with money has been profoundly altered by technological advancements such as mobile banking and quick peer-to-peer money transactions via smartphone apps.

Therefore, financial institutions have begun to implement big data and analytics solutions.

According to IDC, financial institutions have contributed 13% of all global funding for big data solutions.

The incorporation of big data analytics into the financial sector’s business model has been made possible by technological developments. While enhancing the banking customer experience is an important goal for the future of big data, fraud prevention is currently the driving force behind the implementation of big data solutions in the financial industry.

The U.S. Department of Justice estimates that annual fraud losses at financial institutions total billions of dollars and that a serious security breach might cause irreparable harm to the institution’s brand.

Information security analyst positions are expected to increase by 28% in the United States, according to the BLS.

Experts in this field are generally employed to keep an eye out for fraud and other forms of security breaches.

Credit card data, loan details, Social Security numbers, tax returns, and other sensitive information may be compromised if these systems were not properly protected.

When large amounts of data are paired with artificial intelligence (AI) that is capable of machine learning, fraudulent behaviour patterns can be identified with more ease than ever before.

Also, with the help of big data, financial institutions can monitor and analyse customer behaviour, making it easier to spot instances of fraud. Quantitative analysts are in high demand in the banking sector because of their ability to use cutting-edge analytical methods in the battle against cybercrime and other forms of computer fraud.

Quantitative analysts integrate mathematical and financial knowledge with business acumen and computer savvy to improve the models used by financial institutions to manage risk, boost profitability, and delight clients.

2. Integration of Big Data in Government Entities

Public sectors all around the world can benefit from the insights provided by big data and analytics, which can be used to enhance areas such as public safety, healthcare, and citizen services.

What’s more, the government may use the insights provided by big data to better meet the demands of its residents. Government personnel, for instance, can utilise analytics to monitor health conditions, organise evacuees, and distribute aid after a hurricane.

Governments can now analyse data using big data analytics. That’s great news since it means they can stimulate the economy by applying their findings to many industries.

It may be used to keep an eye on civic infrastructure to make sure it gets the updates it needs without costing residents any more than they have to. Information also aids policymakers in making more informed decisions.

Governments can gain the insights necessary to develop policies that are long-lasting, economically sound, and comprehensive by collecting data from a variety of fields, including healthcare, finance, and education.

3. Better Healthcare with Big Data

The health business is increasingly dependent on digital data, which is fueled by the proliferation of EHRs, medical imaging, pharmaceutical research, and patient portals. By collecting biometric data from patients, wearable gadgets like Fitbits can aid in the management of chronic diseases like diabetes.

To encourage healthy behaviours, some health plans offer discounts to members who maintain a regular exercise routine.

 Value-based care, in which hospitals are compensated for the results they achieve for their patients, is gaining ground. Value-based care can only be as good as the information it collects about its patients and their experiences.

One paper in NEJM Catalyst explains how big data, when used correctly, can enhance clinical diagnosis and scientific inquiry.

Healthcare data analytics will ultimately succeed or fail based on its ability to identify and resolve issues. It is not only difficult to obtain a complete picture of a patient’s health and financial status due to the widespread nature of medical institutions, government agencies, and insurance firms, but this information is also subject to strict regulations.

In order to minimise the possibility of making mistakes when analysing the data, analysts must first reformat and “clean” the data. The IT department must engage with the medical staff and the administration to earn their trust and then show them how to set up their IT infrastructure so that it can accommodate big data analytics and improve the quality of care they provide.

4. Improved Data Analytics across Multiple Clouds

Cloud platforms like Amazon Web Services, Snowflake, and Microsoft Azure are becoming increasingly popular for storing data, and networks are being set up to disperse data storage over many clouds. However, data dispersion between on-premises and several cloud environments might complicate corporate analytics initiatives.

In 2022, more organisations will utilise software like Alluxio Data Orchestration Platform, Qlik Forts, and others to access data from numerous on-premises and cloud systems in one place and get insights from that data.

The traditional data warehouse, in which data is collected and handled from various sources in a single area, is giving way to other options, such as gaining a virtual perspective of scattered data and accessing it using common business intelligence tools.

Conclusion

The demand for skilled data analysts to dig through large data and draw conclusions is rising in tandem with its volume.

In fields as diverse as healthcare, government, and finance, big data analytics offers promising new ways to effect positive change.

With the help of Big Data Analytics, data analysts can make a positive difference in people’s lives by reducing the prevalence of fraud, facilitating the distribution of aid during a natural catastrophe, and enhancing the standard of medical treatment available to the public.