Scott Koegler

Scott Koegler

Scott Koegler is Executive Editor for Big Data & Analytics Tech Brief

Analytics is a Top Use of Big Data  

Every day, your organization receives an abundance of data generated by the customers and daily transactions. This ranges from emails you open, mobile apps you use, tags on social media, online purchases, conversations with customer service representatives and even files you generate and save on company computers. Employees, supply chains, marketing teams and finance teams generate a lot of data too. All these sources are stored in your organization electronically or manually. Big data is an extremely vast volume of data and datasets that come in diverse forms from different sources. On the other hand, big data analytics is the complex process of examining this vast amount of data to uncover patterns, correlations, trends and preferences of the customers to help make informed decisions.

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Ready to Start Using Big Data?  

Over the past two decades, data has emerged as one of the most crucial points that professionals in different sectors have continued to discuss. With the importance of data in decision-making, businesses in sectors such as healthcare, financial services, and agriculture are turning to big data as they seek to enhance efficiency and add untapped value to their operations.

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Storage Resources Are Not the Only Issues for Big Data

Data has become a new goldmine for organizations. In the current age, no organization can function without data. With the huge amounts of data emanating from various sources every second from business transactions, social media, customer logs, and stakeholders, data has become the fuel without which companies cannot move. All the data is piled up in a large data set called Big Data. The big data needs to be analyzed to help in decision-making. Big Data has various challenges, including handling it in the best possible way. This involves processing, storing, analyzing massive amounts of data on various data stores. Here are some of the challenges that come into play while dealing with big data.

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