Business management today has really come of the age, with the advent of IoT, generating trillions of data every day. This humungous amount of data is beyond the scope of traditional data management methods, to make out meaningful information. These huge data generating every second across business sectors are also known as Big Data, which challenges every data analysis and storage procedures.

Thus, an out of the box Big Data engineering method, is the need of the hour, if organizations wish to get an edge in the competition. The dynamic nature of business activities today needs fast processing of information from captured source data. To throttle business growth organically, organizations should go for those technology partners, who can deliver the latest Big Data management, across all business verticals.

It is essential to conduct a detailed system requirement study, before assessing the platform readiness, for implementation of Big Data management program.  Big Data management should pave the way for predictive and behavioral analysis of the business stakeholders.

Essentially, Big Data management takes into account all the data entry sources like mobiles, laptops, RFID( radio frequency identification) devices and other wireless sensors. Effective management of these entry points would inevitably lead to the capturing of quality data, which can be further processed to get real time information. Business data growth can be conceived as three dimensional, as in expanding volume, data generation speed, and range or source of data capture. An effective management of this triad will fuel effective decision making through actionable insights.

According to Gartner, business intelligence and analytics would be the top priority in the CIO’s list in the coming years.  With the onslaught of cloud technologies along with social media, there has been an exponential increase in the data generation velocity, which calls for an agile and scalable approach, to data management.

Business houses should choose technology partner, who works with the best proven methodology in Big Data solution.  It is extremely important to find the right approach in collection of the connected data. One should take into account every data silos and touch points, to facilitate effective decision making, promptly.

Every layer of business has to be covered while implementing Big Data Solutions, which would lead to a robust security embargo.  With effective implementation of these policies, organizations will be able to generate new customers, retain the existing ones and increase revenue.

Every captured data must be processed with advanced analytical tool and method, to arrive at meaningful information.  The chosen methodology should take into account then data connection, content, customization and cloud platforms into account.

The technology partner should present the organization with a clear implementation roadmap, stating every aspect of technology evaluation and platform preparation procedures.  It is highly essential to build a central data warehouse, which would accumulate data from heterogeneous sources. With advanced data archiving methods, the integrity and quality of the data is maintained, by moving unused static data to an auxiliary location, for long term retention.

Now this data warehouse is the centerpiece of organizational data infrastructure, which is well complemented by data warehouse offload, which contains ETL(Extract transform load). This is the process of extracting data from the source system, transforming it to the required form and loading it to the targeted system, for in-depth analysis.

The transformation process is designed on the basis of business requirement, in which data can be combined from various industry interfaces.  The above is complemented by ELT (extract load transform) architecture, in which the data is fed into the targeted system and then transformed according to the business needs. The technology partner should guide the organization, about the benefits of both the abovementioned process, as per their business needs.

Another, latest Big Data solution includes the setup and usage of data lakes, which are nothing but large storage repository, holding vast amount of unused data. These data, is stored in its native format which can be quickly retrieved, when needed, thus taking the unnecessary load of the main system.

Advanced stream analytics procedure can be used to process data, when a business even occurs, with its real time ingestion and data processing and storing capabilities.  Organizations should have the capability of advanced analytics along with a highly interactive and informative dashboard.

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