Big Data is one of the most popular buzzwords in the business and IT worlds. With faster computers and larger amounts of processing power available, the ability to mine information from large diverse data sets is becoming a reality. Ongoing test projects are showing the untapped potential this new world holds. The fact is that it will transform many industries.
Just saying the phrase though does not make the data come together in logical and meaningful ways. You need to have the tools to view, analyze, and visualize the data. That is the current challenge of Big Data.
Here are seven mandatory requirements for any big data application:
1. Easy data exploration - Most companies have no real idea of the potential information lurking in their data stores. Exploration of these data sets needs to be easy and flexible.
2. Efficient analysis - The data application needs to offer efficient ways to set-up algorithms for data analysis. And it should allow many users to set-up and use algorithms to analyze data sets in different ways.
3. Visualization tools - People relate to data more when it is in a visual form. Rows of numbers mean nothing. A graphical representation can offer tons of information in a single glance. The application needs to provide built-in tools or use third-party tools for visualization.
4. Personalization - The application needs to allow each person to personalize their view of the data. For example, a user in accounting needs different insights than a person in the R&D department.
5. Collaboration - Beingable to share insights and data between colleagues allows for a deeper level of understanding. It amplifies the value derived out of the analysis being done.
6. Integration - Having the ability to link multiple data sets can offer even more depth than just using a single one available. A good application will take a programmatic approach to allowing multiple data set integrations.
7. Enabling action - The data algorithms and analysis need to feed into the business' priorities. Being able to set up goals and rules in the software that correspond to the business' needs is crucial for realizing the potential of Big Data.
Data analysis cannot work without the right tools. Any application written to explore Big Data needs to be flexible, easy to use, and allow for personal and group work to happen. All of this feeds into how this data work will eventually fit into the business and into transforming industries.
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