5 Best Practices for Reaching Big Data Excellence
SnapLogic’s most recent webinar featured Mark Smith, CEO and Chief Research Officer at Ventana Research, a leading benchmark research and advisory firm. The webinar keyed in on how to make full use of big data through data integration. The real focus though was on the management of information flowing into enterprises from sources that are sometimes incomplete and/or incompatible. Most organizations lack the necessary tools to automate these processes, which can make the data difficult to manage. Instead of using tools not precisely made for practicing big data, Ventana Research suggests that technologies expressly designed to handle big data integration should be implemented. The adoption of the appropriate tools can create a competitive edge if deployed correctly.
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Smith outlined five best practices for reaching excellence in big data integration:
Evaluate efficiency of processes:
Businesses waste resources on data integration tasks. Organizations need to become more agile and DI solutions that have the flexibility to deliver cycles of processing need to be able to meet a plethora of needs.
Examine new approaches:
Many organizations feel as though their technology is too slow, their infrastructure is not flexible enough, and their IT departments are inadequate.
Evaluate technology needs:
Usability and reliability are keystone factors in the selection of data integration solution software technologies. The technology needs to match up with company objectives such as business improvement, analytics and BI initiatives.
Investigate dedicated technology:
Only 12 percent of organizations use dedicated technology for data integration. These solutions can do so many things, including automation, which saves money and frees up IT departments to focus in on other high impact projects.
Gain benefits that outweigh costs:
The purpose of integrating data is to streamline it all into one, easy-to-use entity. Organizations depend on this data, and it helps them to discover patterns, thus giving them insights on where research or investing needs to go in order to become more profitable.
Takeaways:
Streamlining data integration seems to on the minds of many in the industry. Since using big data to create insights and ROI is no longer the new, shiny toy it once was, what is done with that data in terms of integration will be the topic of discussion in the immediate future. DI solutions need to be functional, provide ease of use, and prove to users that they can help save time, money and manpower. Most importantly, solutions providers need to prove to the enterprise community that they work.