Difficulties of traditional data platforms

traditional_data

Evolution of traditional data platforms is started from manual paper works where data are stored in papers in a file. The data are bulky in this system and there’s a maximum possibility to have more duplicated data. A large number of people work day and night to store the data  and analyze it. Then organizations started their investments in centralized database systems where disadvantages of manual paper works are totally eliminated. Still people started feeling many difficulties with centralized data platforms such as

Evolvement of new data source

Due to the development of new sources based on the distributed database which are not processed by the traditional data platforms, which become a top preference for organizations to shift from centralized database platforms to distributive data platforms.

Unstructured data

Processing the unstructured data from various big data source is tougher. Traditional database supports unstructured data only to a short extent. When it comes to an entire organizations , big data platforms are required.Unstructured data from the social media like Facebook, Twitter, LinkedIn etc plays a vital role in organizations development which can be analyzed with big data analytics.

Expensive and timely process

Traditional data platforms are very expensive. Gathering the structured data from a traditional database is not a burdensome. But analyzing and visualizing it always takes plenty of time. Complete team should work with the data from the database to analyze the data which increases the investment of the corporate.

Quicker Analytics and decision making

Decision making to achieve success is the primary goal for all organizations. Quicker Analytics of up-to-date leads to proper decision making. Organization can’t acquire real time data immediately with traditional database. With big data analytics load terabytes of up-to-date data and achieve quicker reasoning.

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