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Top 10 Disruptive Big Data Trends for 2022

The global big data market revenue is projected to hit the 103 billion US dollar mark by 2027. And, the current BI and analytics software market are valued at 16 billion USD globally.

Apart from the stats that speak a thousand words, big data, in association with AI, ML, and other technologies, is fueling what we call the Fourth Industrial Revolution. Big data analytics is one of the most powerful technology trends and is reshaping numerous business processes and operations across the world.

Rapidly expanding IoT networks, Data as a product, quantum computing, and data use for hyper-personalization – there are many emerging trends in the big data segment.

Big data is also being used with AI, ML, and other innovative processing technologies to analyze, process, and parse the massive datasets in multiple sectors, such as Healthcare, eCommerce, Government Data, Public Infrastructure, Banking & FinTech, Security, Manufacturing, Natural Resources Management & Harnessing, etc. 

The latest studies reveal that in just 2 years, Big Data has spurred a change in the business perspective across the entire globe.

It forced business organizations to rethink their:

  • Business strategies
  • Data storage and management
  • Data processing
  • And, conceptual data-related functions

The following visual shows the major potential applications of Big Data, AI, and other technology landscapes:

With more than 2.5 quintillion bytes of data being generated daily. it is more than safe to assume that Big Data is gearing up for changing the way we think!

Here, we are sharing the top 10 Big Data trends in 2022 that are going to be the major change drivers. 


Top 10 Big Data Trends for 2022: Revolutionizing the Core of Modern Business Landscape

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    1. AI Will Continue to Improve, but Humans Will Remain Crucial

    The rise of artificial intelligence is empowering businesses and industries across the globe and empowering people with unprecedented capabilities. While the general perception is of “massive overlays and mass firings“, the experts say that humans are still going to be “crucial“.

    A recent Forbes feature outlined how robots are not going to wipe out the human task force. Further, an MIT study suggests that AI will continue to fuel massive innovation across the globe, and will create many sectors for growth and employment. 

    Hence, it will improve the human race and the way we live, work and grow. 

    However, in order to keep the social and economic divide contained, the stakeholders have to have some common goals to adhere to, such as:

    • Creating policies and regulations to ensure that AI is directed at the “common good” of the humanity
    • Improve human collaboration across global stakeholder groups
    • Prioritizing people over the entire “race with the robots” sentiment

    Also, humans have a distinct way of learning, perceiving, and responding to things, incidents, and people around them. Hence, while the future might have smart AI-powered customer staff, the overall management of operations will still require humans. 


    2. Business Intelligence in Every Walk of Life

    Business intelligence or BI is already bringing changes in multiple sectors, namely marketing, consumer services, customer experiences, and the entire eCommerce segment. The value of the global BI and analytics software market is expected to be 17.6 bn USD by 2024. 

    The flawless and efficient data processing capabilities of BI software help companies around the world to accomplish their corporate and data goals without any hassle. 

    Apart from the current sectors employing BI, such as supply chain management, resource management, and customer interaction management, it is expected to revolutionize the technology and manufacturing sectors as well.

    BI software draws its strength from:

    • Data preparation
    • Analytical querying of prepared data
    • Distribution of KPIs 
    • Use the information to drive business decisions

    Take a look at some of the future applications of BI:


    3. Predictive Analytics

    Big data is empowering business organizations and data analytics stakeholders with its fundamental approach for quite a time now. It helps them to gain a competitive edge and accomplish their goals, such as better services, more sales, more customers, happier customers, and so on.

    Business organizations use multiple tools to achieve these goals and predictive analysis is a common feature of these tools.

    Predictive methods use historical events and modern data to uncover hidden trends and present actionable insights, such as:

    • How many customers are going to leave your brand in the next 5 years with the current business approach?
    • How many products can you sell in the coming quarter and what are the potential risks involved?

    All in all, predictive analysis offers you a realistic and data-driven future prediction for various things. With advancements in Big Data, AI, ML, and other technologies, predictive analytics is all set to gain more power and offer more crucial insights. 

    So, you will be able to predict customer response, churn, purchase behavior and optimize your brand offerings, services, and business agendas accordingly.

    The visual shows how predictive analytics can identify the meaningful patterns of big data and generate future predictions to identify the value proposition of various options.


    4. Cloud-Native Analytics Will Become Necessary

    Gartner says that by 2022, public cloud services will assume a mandatory stance for 90% of data analytics innovation and processes. As data analytics will move to the cloud, cloud-native analytics will become a necessity for all the leaders and industry stakeholders. 

    Cloud-native analytics will empower the data analysts to align the right services with the right use cases, which might give birth to governance and integration overheads. Apart from an in-depth analysis of the cost and pricing models, the data and analytics leaders will also be required to prioritize workloads to exploit cloud capabilities. 

    Some other additional responsibilities will include:

    • Cost optimization
    • Acceleration of large scale innovation and change management  
    • Large-scale migration to the cloud

    Some of the sectors that are in for a huge wave of change in the light of cloud-native analytics are:

    • Government and public infrastructure
    • Healthcare and Life Sciences
    • Travel
    • Mobile and entertainment
    • Retail & eCommerce

    Because of the inherent advantages of cloud-native platforms and analytics, such as elasticity, self-service, monitoring, etc, industry leaders consider cloud-native platforms mandatory in order to succeed with Big Data. 


    5. Digital Transformation

    Digital transformation stems from the ability of an organization to combine both automation and digitization. 

    As the global business landscape becomes more competitive, more sophisticated, and extremely data-centric, Big Data emerges as one of the key drivers of digital transformation. Businesses across the globe utilize huge chunks of unstructured data to discover the hidden patterns in relation to their business models and Big Data becomes all the more important. 

    Take a look at some ways Big Data triggers digital transformation:

    • Big data analytics offer granular insights about specific customer clusters
    • Big data analytics for delivering highly tailored services to specific market segments
    • Implement future data predictions to make businesses more aligned to customer expectations
    • Utilizing massive data stores to actually drive growth and streamline business processes

    6. Climate Change Research

    Climate change research comes under the umbrella term “X Analytics” that is coined by Gartner. “X” stands for a data variable for a wide range of structured and unstructured content, such as video analytics, text analytics, and audio analytics.

    Leaders in the data analytics segment utilize X analytics to solve the toughest challenges to humanity, such as disease prevention, wildlife protection, and climate change. 

    Big Data, in unison with other technologies, such as artificial intelligence can comb through millions of research papers, news sources, clinical trials, and academic content pages to help climate researchers. The researchers can find new ways to contain the massive climate change, create containment plans for severe outcomes in red zones and identify the most vulnerable population pools via graph analytics, etc.

    Take a look at the following visual that shows various ways big data can benefit climate change researchers:

    Big Data analytics will also empower climate researchers to predict and plan for natural disasters and other such crises with its predictive models.


    7. Medical Cures and Pandemic Control

    In the pandemic-struck world, big data analytics and artificial intelligence assumed an extremely reliable stance in procuring the most reliable information at all times. Apart from helping in the research and development of novel treatment procedures, Big Data offered possible opportunities and sources of the right information, such as patient records, COVID tally, patient-reported travel, etc. 

    Medical experts use the term “precision medicine“, where medical experts are able to design a highly precise treatment procedure via big data analytics.

    When it comes to developing the best treatment procedures, there are two ways:

    • Classical Methodology: Stems from a priori hypothesis and no reliable insights from historical data
    • Big Data Analytics: Hypothesis generation from experimental and historical data 

    Precision medicine is a synergistic result of the classical methodology and Big Data, as shown in the image below:

    Researches reveal that Big Data greatly enhanced the abilities of medical researchers in understanding the dysfunctional parts of Biology. Further, the medical experts are all set to use Big Data to deliver pragmatic value to clinical practitioners as well.


    8. Fantastic Business Capabilities via Big Data Fabric

    Big Data Fabric is an emerging concept of a platform that can accelerate and refine business insights. 

    As per Forrester, the platform will automate the ingestion, discovery, curation, integration, and preparation of data from data silos. 

    Hence, the business organizations will have a set of data services to deliver capabilities across all the business verticals and a choice of business endpoints, in a consistent manner. Further, the platform will standardize data management practices and practicalities across hybrid multi-cloud environments. 

    Offering unparalleled analytical services, the big data fabric will empower the business networks with enhanced security across the cloud networks, on-premise systems, and edge devices. 

    A simple visual representation of big data fabric is shown below, with various components and functions:


    9. Augmented Data Management

    Deloitte and Gartner cite Augmented Data Management as the latest technology trend and suggest that coupling it with AI and ML can unlock various benefits for data management. 

    ADM or Augmented Data Management is an application that enhances the ability to automate data management tasks. Hence, ADM is a worth-betting trendsetter in the big data landscape in 2022. 

    ADM empowers organizations in two ways – making data management more streamlined and easier; and facilitating automation. Coupling ADM with AI will reduce the time, effort, and complexity involved in the automation tasks. Further, you can leverage the current data management platforms for experiential learning with Augmented Data Management. 

    According to the industry experts, the areas where ADM has the most potential are:

    • Metadata Management
    • Data Quality
    • Master Data Management

    10. Data-as-a-Service (DaaS)

    Data-as-a-Service (DaaS) is not an entirely novel concept, as it has been in use for quite some time now. DaaS refers to a data management strategy using the cloud for delivering multiple services, such as integration, storage, processing, and analytics. All these services are delivered over a network connection.

    However, earlier delivering these services was a daunting task as the network bandwidth was a limiting factor, and data processing capabilities were also limited. 

    With Big Data analytics, Data-as-a-Service is gaining momentum, and by 2023 the market size is predicted to hit the 10.7 bn USD mark. 

    While the majority of these models are enabled by SaaS tools, the trends are going to change in the times ahead. If you are a business organization with hoards of data that is useful to people in general and are facing issues maintaining and managing it, DaaS can be a lifesaver!

    Some of the compelling benefits DaaS offers are:

    • Simplified data access from any device and anywhere 
    • Cost-effective data use and data sourcing
    • Easy update and monitoring

    Big Data Is the Answer: Whatever the Question Is!

    With such promising trends and many more upcoming ones, big data is undoubtedly all-set to revolutionize multiple business sectors, processes, and public infrastructure in general. 

    However, with greater capabilities and functionalities, comes the load of developing better and more reliable security postures, and cost-efficiency models. While the world is still gearing up for embracing the set of new duties that are taxing enough, the hybrid data analytics and computing landscape are teeming with disruptions. 

    And, Big Data is the answer, irrespective of the question we have!

    Solve your business problems with the help of Big Data Analytics

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