Scott Koegler

Scott Koegler

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

Integrating Big Data Can Be A Challenge

Big data integration is a critical step in any Big Data project. However, some challenges and issues must be taken into account while integrating data. With the growing number of data consumers, big data integration can become a problem that any company needs to respond to. Although it may sound easy, big data integration is not simple as it sounds because large data sets that are structured, unstructured and semi-structured are involved. All these diverse data sets are to be stored in a data warehouse for later retrieval. Some of the challenges encountered during data integration include uncertainty in the management of data, synchronization across data sources, availability of skills and getting the right insights. Despite these challenges, managing integrated big data makes decision-making accurate and ensures the decisions arrived at are insightful.

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Big Data for Small Businesses

It is hard to come across a talk on technology without hearing how big data will alter the corporate landscape. As big as the name suggests, big data is never too big for small businesses. In fact, with the right adoption of this technology, small businesses can gain significant insight that can allow owners to discover hidden trends, patterns, customer preferences and other crucial insights that are good for proper decision-making. With the help of big data, small businesses can make significant business decisions that are necessary to stay ahead of the competition and increase profitability. While most people know that big data can help small businesses, some of them are not clear on what ways they can benefit from it. Here are some examples of how small businesses can use big data.

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Your Big Data Can Send Your Performance Skyrocketing  

Every organization today is thinking of how it can get maximum value from the information it gathers from daily transactions. With the new technologies emerging leading to a massive collection of data more than ever, many organizations are struggling to find ways to obtain value from data and compete appropriately in a fast-paced marketplace. However, they keep asking themselves how best to achieve value. Knowing what happened and why it happened is no longer enough. Rather, organizations must know what is taking place now, what might happen in the future, and what actions should be taken to get the best results.

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