By Manish Gupta, CMO, Liaison Technologies
While apps and processes are the enablers for business users, enterprise data are the assets that drive operational performance. Next to user experience, extracting value from its data should be a strategic missive for all organizations. It is integral to achieving return on investment (ROI) and risk management objectives, strengthening competitiveness and meeting GRC (governance, regulatory, compliance) requirements. The more data-centric a company is the more likely it is to outperform its peer group on financial metrics and market valuation.
Monolithic applications are becoming less relevant to the enterprise. Agile DevOps practices and HTML5 for cross-platform development continue to fuel rapid growth in cloud and mobile applications. While these apps can be launched faster and updated continuously, they increase complexity due to the many disparate components that comprise composite apps. And with more apps, come more sources of data to integrate and manage.
Traditional, on-premises data integration systems are straining under the weight of unabated data growth – from both legacy systems and big data sources. Legacy providers with bolted-on cloud capabilities often make it harder – not easier – for enterprise IT to integrate and manage the unstructured data alongside their conventional structured data.
Meanwhile, users are demanding faster access to more data sources. IT teams face increasing pressure to provide the data sets that business users need in a timely fashion. And it is more likely that these data sets draw on data from OLTP and OLAP systems in combination with newer NoSQL or Hadoop-based formats.
Big data challenges traditional data integration and business intelligence (BI) systems. Capturing and analyzing social media, Web server logs and other forms of machine data add another layer of complexity to the BI data integration process. And while a data lake proposes to help with data management issues, it does not address the potential for new or expanded silos that cloud and mobile apps threaten to perpetuate.
Decision-making is either stalled or flawed, as insufficient – or worse – inaccurate data impedes model building and validation. Time-to-value suffers. Outcomes are sub-optimal at best, and potentially catastrophic in the most latency-sensitive environments, such as high-frequency trading desks or hospital emergency rooms.
It’s Time for Next-Generation Data Integration and Management
More data-driven organizations have recognized the need to speed the availability of data that end-users need for analysis and decision-making. Next-generation BI tools, with easy-to-use data visualization capabilities are becoming more pervasive. By pushing these tools further down into the organization, management hopes to improve business operations at the point of decision – usually where the customer is.
A born-in-the-cloud data integration and management platform is better suited to handle the melding of data from newer composite apps and legacy systems. Such a platform is more scalable and flexible to bridge existing enterprise infrastructure to modern development practices and platforms.
This is not simply an iPaaS platform that facilitates the integration of data among and between clouds – whether private, public or hybrid. While incorporating that functionality, a next-gen data integration platform with data management capabilities not only provides orchestration and adapters for a much broader array of apps and data sources. It also provides a stack to manage the data these different sources generate.
A next-generation data platform that combines integration and management enables IT to improve its service levels to the business. It facilitates the adoption of cloud and mobile apps, enabling the organization to transition to consuming technology as a service. Users get faster access to the data they need, lifting productivity and improving decision outcomes. Customer service and satisfaction rises as a result of more engaged employees.
Unified data integration and data management helps enterprises improve business processes and become more responsive to end-user requirements. Customers gain agility and flexibility using an extensible, high-performance service-oriented platform built on the latest state-of-the-art infrastructure and tools that easily integrates all data sources. By focusing on the data that drives operating metrics, IT can also more closely align with business users to ensure data governance best practices and more efficient application development and service delivery. These are the characteristics of leading data-driven enterprises.