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Avoid Data Sharing Lock-in and Take the Open Road

Avoid Data Sharing Lock-in and Take the Open Road
There is a lot of hype today around data sharing and the value it brings to your business. But what exactly is data sharing, and why should you and your company care? In its broadest form, data sharing is when a provider or creator of data shares that data with a consumer or users. The reality is that the hype in the market today is really focused around solving the problem of how to share data effectively and easily with trusted internal and external entities for improving existing business processes, creating new ones, or generating new revenue streams by monetizing data.

Sharing data is nothing new. Companies have been doing it for a long time. Traditional on premises customers have been sharing data with other divisions and business partners by allowing direct access to shared data in databases through portals or simply using data extracts and FTP to share data externally. What is driving the big change in data sharing is the move to the cloud and how companies can share data in the cloud.

When it comes to data sharing, I believe that for companies to have the most efficient, flexible, and economical cloud data sharing solution, it is critical they leverage an open sharing strategy. What do I mean by open strategy? One based on open data standards and data marketplaces.

One method that companies can use to share data is by leveraging shared storage in the cloud. Typically, this is done by putting the data that is to be shared in an object store and providing access. In an open data sharing model, the data would be in the object store in an open data format. An open data format, or open file format, is simply an open format for storing digital data, defined by a published specification usually maintained by a standards organization, which can be used by anyone. Some common examples of these are CSV, JSON and Parquet. Why as a business do you care about this when it comes to data sharing? It comes down to flexibility. The ability to be flexible directly impacts cost as well as time to value when it comes to data sharing.

Since the shared data is in an open data format, both data producers and consumers are not limited to a single vendor or piece of technology in publishing and accessing the data. For example, if you are sharing data with business partners leveraging the cloud shared storage method, a platform like Teradata Vantage can publish shared data to an object store in an open format like Parquet. Your business partners can then access that shard data with ANY tool that can read and access Parquet. That means that they can leverage another instance of Teradata Vantage, or a wide range of other commercial or open-source engines such as SQL Server, Starburst Enterprise, open-source Presto, Spark, Hive and numerous other tools. The benefit of this is that both you and your business partners can utilize your EXISTING tools and skill sets to access and analyze shared data. This means quicker time to value, lower overall cost, as well as the benefit of not being dependent on a single vendors tool or platform to share data.

Many of the same benefits that open storage sharing provides are also true when it comes to leveraging the cloud vendors open data marketplace. In an open cloud marketplace, like the AWS Data Exchange, you can share data both privately and publicly. The data exchange allows you to access and analyze shared data with existing engines and tools. The data marketplaces have the added benefit of providing all the out-of-the box, needed components that are necessary for an efficient sharing environment. Features such as data logging and lineage, authentication, authorization and security, encryption of data and at rest are provided in the marketplace. The marketplace also makes it extremely easy to monetize your data, handling all the components around charging consumers for data.

The centerpiece of Teradata Vantage’s data sharing strategy is one of open data sharing. We believe that providing data sharing capabilities around Vantage that is centered on open sharing will provide the most flexible solution and drive the highest business value for our customers. Though some other vendors tout that they can support open sharing, the true focus of their solution is really one around a proprietary and closed environment. It is key to understand that open sharing is the foundation of our solution. That means our strategy, architecture and R&D is all around delivering the most closely integrated, best, and easy-to-use open data sharing solution, not being peripheral to a closed proprietary solution. Click here to find out how to successfully empower your organization to deliver a flexible, open data sharing solution or contact your Teradata representative.
Portrait of Mark Shainman

(Author):
Mark Shainman

Mark Shainman is the Program Manager for Teradata’s ecosystem management software Teradata IntelliSphere, as well as Teradata Vantage and competitive programs. As part of Teradata’s analytical ecosystem team, Mark looks after the marketing, education, promotion and strategy-surrounding the uptake and usage of QueryGrid, AppCenter, Data Lab, Ecosystem Manager, Multi -System Viewpoint, Data Stream Architecture, Unity and Data Mover, and Teradata Vantage. Mark also continues to be the global program manager for Teradata’s Competitive programs, covering Oracle, IBM, Netezza and SQL Server migrations as well as cloud migrations and data mart consolidations. He has managed the global aspects of technology, strategy, positioning and sales support surrounding numerous products and programs at Teradata. Prior to joining Teradata, he was a senior research analyst for META Group specializing in database management systems for both online transaction processing and decision-support architectures. Shainman has advised clients on a wide spectrum of database issues, including total-cost-of-ownership analysis, data mart consolidation, disaster recovery, replication, and security, while assisting with core database product comparison and selection.
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