There are a lot of buzzwords associated with data integration. Industry experts regard this solution as a circulatory system for sending business data across different enterprises. Smart enterprises are using this solution to create a mesh to integrate different systems and align them with business objectives. Easy querying and retrieving data helps in the smoother moment of data. Enterprises of all sizes can use integration for building an intelligent relation between all technologies.
Enterprise business systems are creating waves of data while executing business transactions. Managing this cosmic growth of data becomes the next big challenge before enterprises. From an IT standpoint, data architectures need to be built with strategic objectives for accommodating multiplying sources of data. To solve this challenge, enterprises need end-to-end integration. Integration provides a future-ready foundation to the processes. It enables enterprises to absorb growing streams of data in a seamless manner. Digital economies need this ability for next-generation initiatives.
Conventional Extract, Transform, and Load (ETL) solutions are batch based. They are highly cumbersome and technical to use. Code based and engineering intensive solutions cannot be scaled to support strategic initiatives. The IT spends a lot of time building these connections and extending them further.
Data integration is a foundational technology for overcoming this barrier. IT teams get a single user interface for moving data between different dimensions. They can connect source and target systems without difficulty and minimum coding. They can use the same connection over and again for exchanging data and building lucrative relationships. In this way, businesses can be easy to do business with and accelerate time-to-revenue. They can improve business opportunities and become more profitable.
Start-to-end integration smacks down functional silos and helps in extracting more value out of the data. It enables latency to transform data from one format to another. The same database can be used for onboarding data. With metadata, more meaning can be applied to data in a way that it can be identified for data-centric operations.
Hybrid IT is poised to become more widespread & complex across digital economies. Enterprises implementing and managing a complex architecture will face multi-GB data processing challenges requiring new approaches. For enterprises dealing with large data, the next round opportunity is coalescing around the data integration. It strategically helps enterprises that have a growing need for multi-GB data processing to expand service portfolios.
Data integration needs to be the first step for modern-day data architectures. New digital economies are rising and taking new forms. With traditional systems waning, enterprises are facing tough times in adjusting their IT to changes.
Enterprises can monetize data by extracting valuable insights from the data. These insights can transform business operations in unseen ways. Start-to-end data integration can allow enterprises to internalize external ecosystems and become easy to work with. Enterprises can improve their operational efficiency, reduce risk or disruption, and garner new efficiencies.
Enterprise business users get the ability to define flows for moving, storing, processing, and analyzing business data. They can eliminate silos and overcome many technical challenges. Electronic data exchange becomes fast, smooth, and efficient. Enterprises can address strategic business needs and adjust their ecosystem as per multiplying data sources. In this way, enterprises can seamlessly replace, re-engineer, or re-engineer their data warehouses. They can establish an overarching business benefits framework that allows them to:
Better manage multi GB data streaming and shorten the data management lifecycle - from ingestion to processing.
Monitor metrics or business benefits and know what actions need to be taken.
Maintain a lineage of data for better business decisions.
Maximize inter-departmental coordination, increase productivity, and business value.
Drive new synergize approaches and enable data pipeline automation.
Scale warehouses to absorb high data volumes from an increasing number of sources without heavy engineering setup.
Support transaction initiative operations with minimal friction and overheads.
It is difficult to imagine any transformation or change management initiative without integration. Enterprises can modernize their environment in incremental phases and update their systems rapidly. Moreover, their IT can be re-engineered in such a way that it can be designed and implemented effectively and address dynamic integration needs with zero-impact requirements.
“Enterprises get access to a lot of business benefits with data integration. It smooths the path for B2B success. Enterprises get a competitive advantage with data integration.”
First, companies beginning to embrace data integration as a vehicle are achieving the best price and performance for moving heavy data workloads. Second, these B2B enterprises are getting concurrent service advantage of cloud & on-premise technologies together. Third, they are harnessing service-level management capabilities and technology integration for allowing governance, monitoring, and compliance across complex partner networks. Fourth, real-time visibility into IT is enabling them to control costs on IT expenditure and find agents of transformation. Fifth, they are now building better offerings for their customers.
Chandra Shekhar is a product marketing enthusiast who likes to talk about business integration and how enterprises can gain a competitive edge by better customer data exchange. He has 6 years of experience in product marketing for SaaS companies.