By Priyank Chandra, SVP – Strategic Solutions, Omega Healthcare
e.The amount of data we generate across the world is astonishing. According to a Domo source, we generate nearly 2.5 quintillion bytes of data. Data is flooding the world at breakneck speed, and we need to find ways to manage it. Extremely large and complex datasets that are difficult to process, manage, and analyze using traditional data processing tools are called Big Data. To understand the characteristics of Big Data, let us break it down into three Vs – Volume, Velocity, and Variety.
Volume refers to the massive amount of data generated every day, Velocity is the high speed at which data is generated and processed, and then there is Variety, which indicates the various formats and structures Big Data is categorised into. Big Data is extremely important in today’s world because it has the potential to assist experts and organisations in deriving insights through data analytics which can drive informed decision-making.
Historical context
Tracing the history of Big Data brings us to two distinct eras that will help us understand how Big Data has transformed the world in the past two decades. The Pre-Big Data era spanning from 2000 to 2010, was a time when the digital landscape was in its nascent stage and the term Big Data held little recognition. During this period, several technological, social, and economic factors caused limitations in data management. The processing powers of systems and servers were severely limited and were unable to efficiently analyze the large volume and variety of data that was being generated at an unprecedented rate. Furthermore, storage capacity constraints and disparate data silos made it difficult to access and share information. The emergence of Big Data addressed many of these challenges by introducing new approaches and technologies for data management.
Big Data management started gaining relevance in 2011 and has continued to address
technological gaps in data management ever since. Big data solutions like Hadoop and
MapReduce facilitated the efficient management of data by distributing computing paradigms and significantly improved processing speeds and scalability for companies. Additionally, NoSQL databases were introduced to handle a variety of data types.
Currently, the rise of cloud computing services is improving the way Big Data is processed and stored. Big Data platforms have also enabled real-time analytics using applications like Apache Kafka, Apache Storm, and Apache Flink. Data processing has also evolved over the past few years resulting in the integration of data across previously isolated silos for seamless exchange of information.
The impact of Big Data in the healthcare IT industry
Big Data is of paramount importance in the healthcare sector because data analytics in
healthcare has led to breakthroughs in disease prevention, diagnosis, and treatment. Technology harnessing the powers of Big Data has improved patient care outcomes by
transforming the ways healthcare organisations collect, store, analyze, and utilize data.
According to Vantage Market Research, Big Data analytics in the global healthcare market is poised to reach USD 79.23 billion by 2028, growing at a CAGR of 28.80%.
In that regard, Big Data in healthcare has also impacted revenue generation in the healthcare sector. The emergence of new technologies has enhanced patient delivery outcomes and has improved operational efficiency. Big Data has made advanced machine learning and predictive analytics more accessible allowing for advanced data-driven decision making. Big Data provides diverse datasets that enable decision-makers to analyze granular details to generate accurate and precise insights.
Since Big Data analytics can process information in real time, healthcare organisations can
make decisions based on the latest information. Additionally, better Big Data practices have
improved data security features which become crucial in protecting patient privacy and sensitive information.
The future outlook
The future of Big Data is bright, and it holds immense potential to transform various industries. The next few decades will witness a data boom due to the exponential volumes of data generated by IoT technologies, Generative AI, and deep learning. Additionally, Edge computing is gaining increasing relevance because more data processing is occurring at the edge close to the data source which has become essential for real-time analytics of Big data. Furthermore, Blockchain technology and Quantum computing are expected to emerge as big players in revolutionizing Big Data analytics and Data governance.
A paradigm shift in Big Data is only possible if those who work with it can keep up with the latest advancements. Hence, Data literacy is the need of the hour. The current workforce will need to upskill to complement the age of automation that is inevitably approaching. The current youth needs to consider courses in cloud computing, advanced coding and analytics, and machine learning algorithms and understand the key Big Data tools like Hadoop, Spark and NoSQL.
While Big Data technologies hold immense potential to pave the way for a data-driven future, one must exercise caution when it comes to data governance related to data privacy, security, and ethics. The only way we can thrive in the ever-evolving Big Data landscape is through continuous learning and adaptability. To summarize, Big Data has had a profound impact in reshaping several industries in the last vicennium, including the healthcare sector. Even as we move toward the future, it is important to note that data will continue playing a pivotal role in problem-solving and decision-making.
