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Agile Computing Authors: Jayaram Krishnaswamy, Pat Romanski, Tim Fujita-Yuhas, Elizabeth White, Liz McMillan

Related Topics: @BigDataExpo, Java IoT, Microservices Expo, Linux Containers, Agile Computing, @CloudExpo

@BigDataExpo: Article

Integrating Globally Distributed Data: A New Approach

The challenges of doing business in today’s “small,” connected world

The era of Big Data is upon us. The volume, variety and velocity of data now being generated is unprecedented in human history. This poses a challenge for those tasked with data integration: how can we manage all this data, particularly across distributed data centers around the world? The complexity and compliance issues of modern data management must be addressed.

Health care organizations, online subscription services, banks and many other businesses need to provide user-friendly service while ensuring trust by protecting and managing critical data. For example, Personally Identifiable Information (PII) that includes sensitive information such as credit card numbers, names and Social Security numbers, can be extremely challenging to manage effectively. There are multiple issues associated with data integration, especially when applied in a cross-regional context that must be considered.

The Challenges of Globalization
Back in the good old days, just a short while ago, an organization's data was easy to control and access because it was typically stored in one location. Today, many large enterprises have a global component to daily business transactions, with customers, partners and employees located around the world. Given the distributed nature of an organization's users and increasing data location regulations, the traditional method of storing data on a central server to support worldwide stakeholders no longer meets business needs.

The effects of globalization are many and varied, adding layers of complexity to business operations. One effect is that many foreign governments are becoming increasingly inflexible about data privacy and security for data originating in-country. While regulations vary by country, there are growing requirements for PII data to remain in the country of origin. This means that policies must be created and maintained to ensure that data is stored in compliance with these regulations, which might be easier said than done when a company operates across continents.

This places companies between the devil and the deep blue sea, as it were. They must store data where it is most convenient and thereby risk non-compliance or set up data stores by region. Each of these brings its own difficulties:

  • Ignoring local requirements: Organizations face serious legal and regulatory implications if they decide to store data outside the parameters of local regulations.
  • Losing immediate access: Organizations must continually consolidate and synchronize their data if they hope to remain compliant by storing data in separate geographic regions. No matter how often the data needs to be consolidated, real-time access to data is not possible.

In the best of all possible worlds, businesses would be able to both adhere to regulations and have real-time access to their data.

A Best-Case Scenario
Data integration technology exists that enables organizations to automate data location compliance while retaining their existing infrastructure, a best-case scenario for protecting and managing data. One approach is an integrated policy-driven data management system that eliminates the challenges described above, by automatically synchronizing data in real time, which provides a holistic view of the data at all times.

Organizations that implement a data integration solution that lets them retain the infrastructure they have, while addressing data location compliance issues, will substantially reduce costs and administrative time. This new approach takes advantage of a "scale-out" architecture where capabilities are extended by simply adding identical data management "nodes" and enables easy scaling either within a data center or to multiple locations around the globe. Integrated policy management virtually eliminates the manual labor usually involved with scaling such a system and delivers a more streamlined, automated process.

It's a Small World After All
Adding data management nodes to existing infrastructure, as needed and where needed, enables businesses to run a data integration solution alongside their current data stores. When a data transaction is completed, most of the data is stored as usual, with region-specific data stored only on the node in that region. For example, if a company chooses to do business in a country that requires all PII data be maintained in-country, it can place a node in that country and the PII data will be stored only on that node, rather than deploying a separate instance of the company's existing database. The nodes create a geographically distributed fabric that provides data visibility in real time.

Nodes can run alongside existing database systems and may also be deployed
in remote locations to enable PII data to remain in the country of origin.

Globalization has changed the way we do business, and some of those changes require organizations to rethink how they manage their cross-regional data. They must find a way to remain compliant with regional regulations while ensuring real-time access to their data. New node-based data management unifies data across different systems and regions, providing real cost savings, real-time data visibility and better response times for remote users. This development in data management helps address the challenges of doing business in today's "small," connected world.

More Stories By Frank Huerta

Frank Huerta is CEO and co-founder of TransLattice, where he is responsible for the vision and strategic direction of the company. He has been published in numerous trade publications and is a respected leader in the database management industry. He has an MBA from the Stanford Graduate School of Business and an undergraduate degree in physics from Harvard University cum laude.

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