In this special guest feature, Anchita Magan from [x]cube DATA writes that the element of quality has to be considered in quantifiable data.
Significance of Big Data
The entire cosmos has been turned into an aggregated ocean of Data – structured or unstructured, systematic or unsystematic, useful or useless. This zillion of roughly organized data is needed to be stored, arranged and analyzed so that it can be brought to use by the business houses to evaluate the dimensions of their success as well as their bottlenecks. Whether a CEO or a COO, a Marketing manager or an operations head, an HR Employee or an IT engineer, they all make use of big data analysis for decision making. But the valid question that arises is ‘which attribute of big data is more important – Quality or Quantity?’
Importance of Quantity and Relevance of Quality
The term’ big’ itself is closely related with quantity. But extracting qualitative and fruitful data out of the bulk is the important task which is needed to be accomplished for sustainable growth, effective utilization of resources and to answer the present and foreseeable challenges. Experts says that we analyze only one percent of Data and hence can tap only 1 percent of its potential. But through systematic data analysis of the rest 99% of data, a revolution can be brought in all the sectors of business era – be it retail, healthcare, telecom, financial services or IT.
But it is also observed that without valid evaluation, collecting hoards of data won’t provide the necessary insights into the business.
Application of Big Data in Health Care Industry with reference to Quality and Quantity
With the boom in Internet and communication technology, big data analysis has gained a lot of significance at the vast global stage. It generate insights on the business performance as a whole by evaluating both the internal and external data collected worldwide.
According to a report by McKinsey five areas with maximum big data potential are health care, retail sector, manufacturing industry, public sector and personal location data. Taking healthcare industry into consideration, which is currently facing major challenges making their services affordable and accessible to all sections of the society and to the remotest of locations. It has been observed that there is an extensive use of health information and health care data which is processed and analyzed to plan, determine and administer the quality of health services and scientific research for major breakthroughs in the fields of diagnosis and medication. The government as well as private organizations provide multiple statistical reports which throw light on the administrative data regarding the expenditure, consumption and utilization of health services, keeping in account the patient’s records, lab records, number of hospitals, bed utilization rates, out-patient visits, occupancy rates, human resources, etc.
This structured and unstructured data can be a guiding light only when it is properly categorized, processed and analyzed to extract the fruitful insights and discarding the useless content, thus turning the quantitative data into a qualitative one. This is achieved through techniques of big data analytics which is a key to the dynamic potential capability of an organization. These big data techniques include text data mining, machine learning and statistical programming, which are backed by widely used technologies like NoSQL databases and Hadoop Framework.
These technologies of big data analysis further helps to control fraud by enabling the auditors to identify the transactions that indicate the activities of artifice or treachery and thus strengthening the anti fraud mechanism of hospitals.
Some applications of big data in healthcare are:
- By combining the most advanced laboratory diagnostics, imaging systems and healthcare information technology, Healthcare Industry enables clinicians to diagnose disease earlier and more accurately, making a decisive contribution to improving the quality of healthcare
- The Healthcare big data technology management offers solutions for the entire supply chain under one roof – from prevention and early detection through diagnosis and on to treatment and aftercare.
- Big data analytics attempts to examine large amount of data emanating from a variety of sources to discover patterns that could be useful in problem solving and decision making.
The best example can be Bumrungrad International hospitals which are effectively using the clinical analytics and Electronic Medical Record (EMR) to deliver better care for its patients, to analyze their needs and to enhance the patients’ satisfaction along with making their service cost effective. The hospital manages patient information utilizing an integrated hospital information system that uses digital radiology systems. A case study by Intel Corporation unveiled that Bumrungrad commissioned the development of a custom total hospital information system to service both the front office and back office, to maximize both safety and efficiency as well as to drastically reduce the potential for medication error.
Thus it is important to understand that the huge amount of big data has to be well examined, reviewed and verified to deduce the useful content; hence adding quality to the quantifiable data.
This article was written by Anchita Magan from [x]cube DATA. [x]cube DATA provides big data solutions and services to companies across various industries that wish to harness the large data sets at their disposal and gain actionable insights from it.