Big Data vs. Metadata: The Difference That Changes Everything
If you are entering the world of digital asset management, you may be wondering what the difference between Big Data and metadata is. Big Data… is it just a massive accumulation of metadata?
Big Data collects so much data that it cannot be examined with standard technology tools. Metadata provides information on a single file, while Big Data offers the ability to update models and trends across the data set. If the metadata is the needle, the Big Data is the haystack. Fortunately, the needle is now “smart”. You can find it…if you know how.
When a digital resource is created, it is immediately associated with metadata about its origin, time, date, format, and so on. This information is no longer sufficient to optimize the organization of work in the company. Each asset must be named, labeled, stored and archived according to defined common standards. A consistent asset management methodology is needed to better find and use them. According to some experts, brand managers spend 35 to 40% of their time looking for assets – a real waste. A good understanding of metadata addresses this problem.
It is also important to highlight the differences between structured and unstructured data. The structured data are the attributes mentioned previously (name, date, format). These attributes are used to archive and store files. They can process, analyze and predict key variables related to your business. Unstructured data is every call, text, purchase, transfer, audio, video, chat, Facebook post or tweet. Servers, devices, counters, and robots all generate data logs that record each action. To become intelligible, understandable, this unstructured data requires prior analysis.
That’s where Big Data comes in. Hadoop is an open-source framework for storing and processing an incredible amount of unstructured data generated by a growing number of electronic devices and connected objects. Businesses can now collect massive amounts of unstructured data and analyze it to make informed decisions. Decision-makers are thus able to anticipate problems before they occur. These unique opportunities are invaluable, especially in areas where blackouts and downtime can have dramatic consequences.
Small businesses do not need to benefit from all the performance offered by Hadoop. On the other hand, they can optimize the use of their resources by standardizing their methods of searching, distributing and archiving resources. Formats and technologies are constantly diversifying. The standardization of asset management has never been so important. It alone can prevent companies from repeatedly acquiring the same asset. With a consistent management, it is no longer necessary to rely on a single controller, responsible for knowing where each file is. If all the employees of an organization speak the same language, the management of the assets is clearly facilitated…And the work also.
Big Data and metadata have something in common: these data will only have the value you give them. Our devices and machines can create more useful data than ever, but they will have no value if you do not know how to interpret and contextualize them, to better find and share.