Data Daiquiri: The Power of Mixing Data

Surrounded by data flowing in all kinds of directions from all kinds of sources, organizations often see themselves data-drown rather than data-driven as they focus on the flood itself rather than the creative power it can infuse in data management practices.

Getting Excited About Connections Rather Than Nervous

Looking at the information deluge from the perspective of smart data helps to see the overwhelming amount of content all around us as opportunities rather than hurdles.

Companies can tap into the underutilized power of the data coming their way by integrating the massive data flows with their own proprietary data. Harnessing the power of these flows becomes possible with the realization that connected, data create a uniform whole with a value greater than the sum of its separate data pieces.

When Life Gives You a Data Deluge, Make a Data Daiquiri

Done right, blending data turns the flood of information into a powerhouse of opportunities to improve services, products and workflows. Mixing data pieces or entire datasets holds enormous potential for plain records to become smart pieces of information, a basis for knowledge, relationships unearthing and correlations discovery.

Case in point, let’s look at the Panama Papers.

When the information first leaked, these were just records. Looked at separately, without links to any other contexts (read other data), they weren’t much of a help for analyzing and discovering connections, but just a pile of names and companies. However, when the Panama Papers got linked to additional knowledge about the world, that is with other datasets such as Wikidata and GeoNames, data became way more revealing and suitable for all kinds of processing and querying.

This is just a simple example of how bringing data together opens new ways of looking at information and making use of it. Among the many other benefits are the opportunities for:

• improving data reuse;
• integrating data sources faster;
• reusing external sources;
• discovering relationships between entities.

All of the above is possible when data are mixed with other data through building links.

Proprietary, Open, Third-Party Data: Shake Well and Serve With Linked Data

It is true that many of the data across the digital landscape are raw, unstructured and heterogeneous (coming from various sources and in different formats). But when interlinked and combined properly, these data enable the breadth and depth business strategies need in the information age.

Every day, millions of data pieces are published by governments, commercial and non-for profit organizations in domains ranging from banking, finance, marketing, stocks, e-commerce, healthcare, agriculture, chemistry. As diverse and complex as these data are, they all fall in one of the three broad types worth considering: proprietary, open and third-party data.

These are also the typical ingredients of a good Data Daiquiri.

• Proprietary data

Proprietary data are the data owned by a specific enterprise: corporate information, financial data, ownership and shareholders data customer and supplier records, website data – basically any data a company is collecting or aggregating.

• Open data

These are machine-readable data published publicly and available for anyone to freely use and re-use. To dive deeper, check out: Open Data Innovation? Open Your Data And See It Happen.

• Third-party data

Third-party data are pre-collected data available from various data providers.

Taken separately, all of these three types of data are extremely powerful. However, blending them is what can triple (pun for geeks intended) their power. Linked Data is that very layer that turns the blend of internal and external data into a homogeneous source.

Linked data are unique for they enable the connection of diverse datasets and thus make information easy to find, share and reuse. Linked Data technologies allow for seamless integration of data from both internal and external sources. Providing a common format for data, datasets are consolidated into a coherent whole and made ready for cost-effective management.

Such standard representation is a solid basis for optimizing business processes, understanding customer behavior and improving decision making.

Combining external and internal data is a cost-efficient solution to the many data integration challenges. Collecting, storing and retrieving data in a way that allows data integration is key to successfully navigating the digital landscape. Click To Tweet

Among the other exciting ways of using data linked to other data are:

• navigating homogenous data;
• building smart queries across various data sets;
• linking more data with no advance planning;
• discovering topics and entities linked implicitly;
• extending data analytics with additional data sources.

Data linked to other data not only broaden and deepen the context a business operates in but also increase substantially the usability of information. Having a profound impact on business practices, connected data cross domains and builds bridges between diverse sources. Criss-crossing domains, data pieces power creative decision making and problem-solving on many levels – all much-needed benefits in a data-driven world where data-driven approaches are a must.

As Sir Tim Berners-Lee once put it:

Letting your data connect to other people’s data is a bit about letting go in that sense. It is still not about giving to people data, which they don’t have a right to. It is about letting it be connected to data from peer sites. It is about letting it be joined to data from other applications.

It is about getting excited about connections, rather than nervous.

Cit. Tim Berners-Lee, Giant Global Graph

With that, here’s to an exciting and successful new year ahead!

Come to join us to celebrate Christmas Eve and New Year with the data daiquiri we’ve mixed together at data.ontotext.com or learn directly how you can do it with a semantic graph database!