Data Structured or Unstructured
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Anytime you hear the word data or big data, a constant stream of green numbers comes to your mind as in the movie, The Matrix. But there is more to data than that.  Data can be structured or unstructured. Multi-structured and semi-structured.  And having structure to data versus a lack thereof makes a huge difference in terms of data storage and analytical capabilities.

Structured data is business’ best friend. Using structured data, organizations are able to construct an enterprise data warehouse, to quickly access data through queries. Structured data is gold, but unstructured data is the growing majority of an organization’s data.

Unstructured data often contains a wealth of information such as consumer buying patterns. The exciting promise of unstructured data is that it enables these non-numerical and not-so-linear flow of information to be combined with numerical, structured information for effective and wholesome decision-making. But this is also a challenge since unstructured data is often heterogeneous and originates from disparate sources from within and outside the enterprise boundary.

New tools such as Apache Hadoop have emerged for storing unstructured or big data.  For extending the data warehouse capabilities to include both types of data, and to respond quickly to business looking for information on their feet requires Data Virtualization which is an abstraction layer between data sources and data consumers.

Let’s take an example of Company X, and see how complex their data management approach is.  For their structured data they have data warehouses and enterprise/Cloud-based applications. For their semi-structured data they have flat files and for their unstructured data they have emails, social media, mobile and cloud data. That is just their data sources. The data consumers, utilizing the stored data, are web services, BI Analytics and reporting tools. Company X, now has an issue of data being stored in disparate silos, and lacks the connection to apply an update to the data across all data silos. Company X introduces Data Virtualization software and solves this by providing faster access to all data, less replication and cost, and more agility to change.

Data Virtualization provides Company X the connection between all the data sources and data consumers by creating an abstraction layer to view the combined data, without moving any of the data sources. Data Virtualization lets the users keep the benefits of their current data infrastructure, subtracts the drawbacks and adds benefits.

Discover the power of Data Virtualization. Connect, combine and publish any of your data from anywhere, anytime and in any format.

Nalini Mohan