Looking at the future

The American entrepreneur, Victor Kiam once pointed out that, “Even if you fall on your face you’re still moving forward.” This is so true for all business organizations in today’s competitive world - isn’t it? Although the future throws open challenges, organizations must keep moving forward and deal with such challenges with the help of cutting-edge innovations. Every decision made and every move strategically taken can define the future course of organizations. It is here, that data science and big data analytics plays a prominent role in helping enterprises (even smaller entities) make informed decisions. Hence, it is vital for businesses to clearly master the concept of big data.

Transforming raw data into meaningful data

Secondary research confirms that, every day a whopping 2.5 quintillion bytes of data gets created. Infact, enterprises collect data from all accessible sources; however, mere gathering of data doesn’t help in taking strategic business decisions. Rather, the collected data needs to be transformed into value-added information to derive a cohesive information. Here comes the critical role of big data, since, it involves systematic extraction of information from large volumes of complex data. The manner in which big data operates, has transformed the mode of operation of many enterprises, who have adopted it in the right time.

The concept of big data loomed large focusing on four key attributes like: volume, variety, velocity and value. The reason why the feature “volume” is essential among all the other attributes is because, the volume of data, both, structured and unstructured contribute towards gaining insights into the business through exhaustive analysis, to ensure consistent growth.

Gaining momentum in decision making

The concept of big data analytics has accelerated the speed of decision making in organizations. Infact, it has not only impacted strategic business decisions, but also created a stir in the mobile app world. Since, the mobile apps develop massive chunks of complex data, thus, in order to solve the data management problem, organizations depend on big data servers. Also, in an attempt to collect and store big data, organizations are relying on technologies such as Cloud computing, Hadoop and Spark. This has minimized the burden of dealing with huge quantum of data.

Are enterprises experiencing a change in the big data way?

How often do you think it is convenient for organizations to combine big data with traditional business intelligence? Although tough, yet it is definitely possible to launch a convenient data ecosystem to generate new insights. For instance, a customer’s reaction towards a new product launch can be readily captured to analyze his/her preferences as well as gauge the existing gaps in the market. Here, the data to be integrated and considered is customer reaction. Now, when this accumulated data is combined with traditional business intelligence, companies do benefit.

Thus, seamless collaboration between big data, traditional business intelligence and enterprise IT operations does ensure success in businesses. Also, in a way this alliance can ensure optimum utilization of big data applications by connecting all the different facets of business operation. Infact, big data analytics help organizations to collect and integrate data, while creating a model to test the applications in real-time. This ensure accuracy and promptness in the process.

Data management within organizational framework

Normally in IT operations, IT specialists only deal with controlling of data whereas, the analysis is done separately, this creates organizational limitations and results in faulty business decisions. With big data in picture, organizational initiatives became more centralized, with a dash of competitive advantage over peers. Big data was widely adopted in the organizational framework, in alignment with organizational goals, proved useful in extracting required information in no time.

That is not all! Further, the emergence of sensors and RFID tags helped in effective analysis of the generated data without the need to store them. This is why big data analytics could be effectively used for tracking and processing data in financial transactions, agriculture, applied science and transportation verticals. It is also a great tool for professionals to gain business intelligence, while at the same time its ability to maintain data security and privacy policies is also worth mention. Strategies formulated by enterprises through big data analytics must adhere to the data sharing norms and polices, this will ensure transparency and even limit any kind of data breach.

Let’s now analyze in detail the impact big data has on critical business decisions, business performance and return on investment.

Customer is the king

Recently, organizations have diverted their focus more towards customers, which is why customer service is of paramount importance these days. With an attempt to retain customers and enjoy a competitive edge, companies are offering customized solutions and services to cater to the diverse requirements of customers. Also, the use of big data to gather actionable insights, through feedback collected from customers can initiate an engaging relationship between customers and organizations. This in turn, elevates the brand visibility and customer loyalty levels. Also, through radical customer insights, big data analytics can highlight leading customer trends. The predictive models available can empower the organizations to meet customer demands and at the same time overpower competitors with respect to price and service quality.

Enhance operational efficiency

As per market research, by 2030, the data gathered in vehicle market will be worth $750 billion a year. More and more companies are leveraging big data to automate and enhance their operational efficiencies. Tesla, for example, embedded sensors in their vehicles to collect raw data, which is thereafter sent to the central servers for analysis and strategic action. This exhaustive process of leveraging big data analytics has helped in enhancing the performance levels of the cars.

Capacity improvement without additional investment

The power of big data is experienced across all industry verticals. It can enhance an organization’s operational efficiency without any additional investment. Sprint, a telecommunication giant leveraged big data analytics to optimize resources and reduce network errors. This improved customer experience and ensured brand value and visibility.