As businesses grow, owners typically incorporate numerous systems to gather and store the important data needed to keep their company's operations functioning smoothly. New platforms are often adopted on an as needed basis and are not integrated to one another, which leads to inconsistencies across data platforms that require information to be manually entered into each system. The problems caused by inconsistent or incorrect data may not seem drastic in small numbers; however, as a company scales, such minor discrepancies between systems can become major obstacles in data verification, retrieval, and reporting. Because data discrepancies can represent significant losses for a company, it is in a business owner's best interest to seek big data integration solutions.
Big data solutions are a series of integrations between disparate systems and automated reporting tools using a centralized location such as a custom database or the Cloud. When enterprise data sources are seamlessly integrated through such intermediaries, organizations can use the collected data to identify market trends, visualize buyer profiles, and develop highly accurate forecasting models that will allow the business to adjust to changes in the buying cycle of their target market. Furthermore, integrating various systems allows users to operate more efficiently while reducing redundancies and increasing data security.
Although adopting big data strategies to manage important business information efficiently is vital to the ongoing survival of the company in the digital age, it is an investment that companies should not take lightly. Business systems must be integrated seamlessly to create an effective big data system. Big data strategies fail when the web service application programming interface (API) integrations do not seamlessly integrate various platforms, particularly when a business uses a combination of legacy systems and newer platforms to collect and store different data sets. This complication can be overcome by hiring integration experts to create custom APIs for each system to allow those systems to transmit data between systems as well as database administrators who will monitor the data exchange and maintain the databases to keep the systems functioning as intended.
Before implementing a big data solution, a company must first identify their business needs to account for the number of users and the amount of data each user will enter in the system over time. For smaller enterprises, a relational database management system (RDBMS) possesses enough storage to easily handle the amount of data needed to access through the database. However, larger enterprises may face data management issues using an RDBMS because the systems are not large enough to handle the hundreds of gigabytes or terabytes needed to store the data for the company, and may need to seek higher volume options or use the Cloud rather than a server based solution.
Big data solutions offer organizations many benefits in terms of improving productivity and enhancing business analytics. By pooling data from distinct systems into a centralized location, organizations will have the tools necessary to stay ahead of market trends, improve customer satisfaction, and increase revenue.
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