The volume of market data, historical prices and transactional data that is stored in disparate systems allows organizations to not only collect the data, but extract value from it. This information came to our attention in Finextra’s article, “Unlocking Data Silos to Reach the Promised Land of Smart Data Analytics.”
Data quality is critical to meaningful data analytics and data analytics are key to business strategy – but with increased volumes and complexity of data coming into organizations, how can they ensure data is of the required quality and analytics are adding value to the business?
Data dictionaries and business glossaries (taxonomies and ontologies, hello?) are used to achieve consistency and help business units understand different types of data. With the immense volume of data, quality can be impacted. Without established standards, data can be less than useful, no matter how much of it a business may have.
Agility is paramount. A business cannot afford to wait until their data is perfect to implement data analytics within their organization. They have to be able to demonstrate the business need and the business benefits of investment in optimal tools and technology.
Melody K. Smith
Sponsored by Access Innovations, the world leader in taxonomies, metadata, and semantic enrichment to make your content findable.
