Data growth is also enormous within organizations, but this largely consists of redundant data. Large volumes of data are routinely sent back and forth on a daily basis, especially between government organizations. In almost all intra-organizational circumstances, receiving organizations store the data in their systems, resulting in more copies of the data. They may have copied data from transactional application databases and operational data stores to private files and spreadsheets.īeyond inter-organizational data exchange, intra-organizational data exchange also takes place. We also find that redundant data copies are stored in development and test environments. Data can sometimes be stored several times within one datastore to support different use cases. Most organizations store customer data in multiple repositories such as a transactional system, staging areas, data warehouses, data marts, and maybe also a data lake. Most of the collected data is not new or original much of it is copied. The Danger of Collecting Dataįor this post, I want to focus on a second challenge, data collection. However, that is a separate topic that I will discuss in a future article about maximizing the time-to-value of data and using data to gain actionable insights. Data has a limited shelf-life, and if it is not analyzed within a suitable timeframe, data is a wasted resource. The first is that much of the collected data remains unused. Organizations face two critical data-related challenges. By 2025, it’s estimated by the World Economic Forum report that 463 exabytes of data will be created each day globally – that’s the equivalent of 212,765,957 DVDs per day! But this doesn’t mean organizations get the most from their data. This growth is due to diverse data generators across consumer and enterprise landscapes, including hundreds of cloud applications, smartphones, websites, and social media networks, with each source generating meaningful data. Every day, organizations collect massive volumes of data that continue to grow.
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