The priority to generate additional value from multiple data sources for organizations is rising. They are not just historical data or real-stream data but even the data which is in motion. There is a desperate need to implement continuous data integration that can drive value for organizations and gain masterful insights. Data integration challenges have proved to be a significant challenge for an organization pursuing digital transformation. In today’s business, data flows real-time across platforms and devices in both offline & online world. How can enterprises take advantage of the high velocity of data by building a good data integration infrastructure is a puzzle for CXOs.

Many organizations misinterpret the data issue as a volume, velocity & variety issue whereas it is a data management & data integration challenge. Typically, organizations either add to an existing model or create a new model. But often they add to the existing one. The challenge for data architects is how much of new or custom work is needed.

Generally, there are a lot of reasons why business data tend to be siloed. Organizations have multiple varieties of data, ranging from the server, network and website logs, digital data, and even offline data. Because of different data types coming from different sources, creating a single process for integrating all the data into a single hub can be challenging. These data come from different business units within the organization which tend to provide different types of information with different access restrictions. For example, even within a sales organization, data may not be shared with different geographies and with different employees within the same country. The complete data may not be available to the marketing team or marketer who is in charge of providing an engaging customer experience journey which may result in a less than expected outcome from any campaigns. So, it is imperative to avoid data siloes and the required data is available to teams to derive the best value from that data.

For instance, modern IT infrastructure tends to be quite diverse & complex due to the availability of new software tools to perform multiple functions in an organization and where exactly growth occurs inorganically through acquisitions or through a franchise. Generally, organizations use a combination of on-premise and cloud systems and multiple operating systems and more. Because of the complexity in infrastructure, logs and other types of formatted data, it makes integration hard.

New as well as old data are usually stored in different locations. Old data is probably archived after a certain period but in contrast, real-time data and new data may remain in their original data sources. This could lead to data silos because data is stored in different places based on the data age.

The key is to understand which data is to be managed and what is the value it provides to the enterprise. With data coming in from all corners it is important to understand where you do want the data.

The key to have better data integration is to have clarity on the following:

  • Is there an effective metadata management strategy?
  • What are the channels through which data is obtained?
  • Where does it reside?
  • What is the value of the data to the organization?
  • How is it shared and interpreted?
  • What is the big picture that the data provide?
  • Who is consuming the data and how is the access getting governed?
  • What are the decisions does the data drive for the organization?
  • How critical is to analyze data with increased frequency to provide greater business agility?
  • Does the data need to be analyzed as it is generated to gain a business edge?

If the organization does not have a grip on the above-mentioned points, the data integration will be cosmetic & chaotic. Assuming good data management practices are in place, there is still a need to identify the right tool or platform to execute data integration initiatives. AURAS, a revolutionary accelerator can help you manage and simplify your data integration projects. AURAS can help you build a data hub that addresses different speeds of integration with industry-leading integration tools or customer ones.

AURAS helps in managing your integration initiative in an on-premise, cloud or in a hybrid eco-system. Tracking and monitoring your data integration can be easily achieved across systems and platforms. Your strategic data integration projects can be hastened and new applications can be integrated rapidly. AURAS, being an efficient tool, provides a single data hub by unifying multiple on-premise or multiple clouds and existing systems. It works with any middleware integration platform that could support customer’s digital initiatives and ongoing integration needs. AURAS is a proven end to end data integration framework comprising of industry-proven design patterns, reusable components, and best practices to speed up the integration cycle at a great pace.

Raghu Raghavan

Awarded 2017 Most Influential MarTech Leaders, World Marketing Congress. Experienced Team leader with a successful track record in Product-Market fit, Product Marketing, Field Marketing, Digital Marketing, Monetization, Business Strategy, Business Development across Technology industry. Expertise in both Products & Services oriented segments.

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