Every industry, be it manufacturing or retail, is faced with growing volumes of data every day. There are numerous sources like sales transactions, business processes, social media, etc. through which a continuous stream of data flows. Hence, an urgent need for this data to be processed is crucial for organizations to reach their goals and progress.
People today have no shortage of options available to them. Consequently, businesses are finding themselves in an increasingly competitive world where only innovation and agility can sustain them over a period of time. The importance of big data technologies has never been realized as much as it is today, for only by leveraging it can businesses adjust and adapt themselves to the dynamic environment.
Big data refers to the vast volumes of data in structured and unstructured formats that an organization receives daily. Just gathering this data is not enough, it needs to be examined and understood in a way so that valuable insights can be gained. The importance of big data in business has been shown in recent surveys. Forbes has estimated a 53% increase in enterprises’ performance and growth that incorporated big data analytics into their processes.
The IT industry has come up with the 3 Vs that constitute the Big Data. They are:
Data is collected from multiple sources. Big Data is associated with the size of the data. Its specific volume is essential to it being categorized as Big Data. Every day around 2.3 trillion gigabytes of data are generated. This kind of enormous volume is one of the foremost features taken into account when dealing with Big Data.
Velocity means the speed or pace of data creation. Data flows at an extraordinary speed and needs prompt processing. The processing speed of the generated data to fulfill the demands indicates the real value that resides in the data. Big Data velocity is directly related to the rate at which data flows from various sources like application logs, mobile devices, to name a few.
Variety refers to the varied types of data, structured and unstructured, that an organization receives. Apart from spreadsheets and databases (structured), data in the forms of emails, videos, photos, PDFs, etc. (unstructured) also needs to be analyzed and considered.
The importance of big data processing is essential for enhanced customer service, improvement in supply chain efficiency, and detection and prevention of risks to products and services.
Big Data requires a stable infrastructure to be dealt with effectively. Big Data technologies collect this data in a systematic manner. Hadoop clusters manage and collect data before its analysis by analytic technologies like data mining, machine learning, and predictive analysis. Hadoop data lake serves as a storehouse of incoming raw data flows. Data is made ready for analysis by HDFC by being properly organized and partitioned.
Some of the software used for advanced analytic processes are:
Machine learning that enables applications to study and predict outcomes.
Predictive analytics, which studies current and past data to make accurate forecasts about future trends and patterns
Using big data analytics technologies, data is extracted, readied, and blended, which businesses can then use for their own analysis. It is used in different ways by organizations and enterprises.
The importance of big data lies in its smart utilization by a company. Data analysis provides an organization with answers to complex problems. Following are the major reasons why Big Data analysis is being leveraged rapidly by businesses all over:
Big data tools like Hadoop and cloud analytics can promote cost efficiency when large amounts of data need to be stored. Moreover, big data tools immensely help in recognizing and finding out cost-efficient ways of conducting business.
The high speed of Hadoop and in-memory analytics, together with the ability to examine new data sources, enable businesses in prompt information analysis. It imparts them with rapid and productive decision-making ability.
Through an effective analysis of Big Data, businesses can discover their customers’ current needs and requirements. Thus, they can churn out enhanced products and services and serve people better. Big data analytics is used to engage efficiently with customers and evaluate their preferences and interests.
As a business grows, so does its data and variety. Much of the important information tends to get stuck in data silos. It remains inaccessible and underutilized. Here the importance of big data tools comes to the fore. Analysts and engineers can navigate through piles of information and arrive at data-rich insights.
Big Data analytics, by uncovering meaningful relationships and patterns, enables businesses to achieve a greater understanding of the customer’s purchasing behavior. Sound knowledge of market conditions enables them to modify their processes and operations accordingly. It also helps businesses in structuring their marketing campaigns effectively.
Predictive analysis has made it possible for healthcare professionals to provide personalized treatments to their patients.
Big data powered digital courses are being leveraged by academic institutions for the holistic development of learners.
Big data has enhanced the supply strategies and the quality of products in the manufacturing sector. By establishing a transparent infrastructure, Big Data helps in forecasting uncertainties that may negatively impact a business.
The vast amount of data that retailers have collected are being analyzed and leveraged to generate customized experiences, enhance revenue and sales, and serve customers better than before.
Thus, we see that the importance of big data in business is immense. The surge in the amount and variety of information has made it indispensable for organizations to process and make sense of it and thrive in today’s competitive environment. Big Data analytics has enabled organizations to achieve a reasonably accurate view of the future, thus helping them to keep innovating themselves in an ever-changing environment.