SCIKIQ is leading the future of data integration by combining different data integration design patterns, utilizing active metadata, knowledge graphs, and Machine Learning to augment data integration and data delivery tasks, across all environments, including hybrid and multi-cloud platforms.
This allows organizations to turn their data into actionable insights that drive business growth and success, and meet the demands of the future of data integration which includes a greater focus on cloud-based solutions, real-time integration, increased automation, Machine learning, AI integration, and Big Data integration.
Roughly over 40% of companies see application integration as one of their top challenges. Enterprise data engineers spend nearly 50% of their time building and maintaining data pipelines. 76% of enterprises said it took days or a week to prepare the data for revenue-impacting decisions.
Your data platform should allow each team to correlate data from different sources (Data Silos), align different application systems to improve cross-team data sharing, should be able to deal with complex integration scenarios with multiple use cases, allow for advanced, bi-directional integrations, offer a scale of integrations and moving data faster for real-time analytics and data availability for the business users. The data integration platform should be able to set data integrations in minutes and save critical time for business users.
The digital world we live in is dominated by hybrid multi-cloud, Multi-Geography, Multi-vendor data systems. This data spread creates a major challenge to conventional data integration methods and strategies.
Data integration strategies in the digital world are changing fast. The world changed after the advent of hybrid multi-cloud and with it, data management strategy needs to evolve of moving and copying data from one system to another to integrate, manage or query data. Hybrid data integration has been in use lately due to its ability to connect applications, data files, and business partners across cloud and on-premises systems. Relational databases dominate the sources and targets for data integration and pipeline support regarding of organization.
Using the right integration platform will allow you to maintain a continuous data flow between the different applications an enterprise is using, while also making sense of the huge amounts of data you probably have already.
One of the best methods to achieve this is through an extensive integration platform. It’s important to assess the capabilities of any solution you’re thinking about before choosing one. Otherwise, you could end up creating bottlenecks later on or end up with the wrong platform. In the future, data integration will continue to evolve to meet the growing needs of organizations.
Some of the key trends that are likely to shape the future of data integration include:
Cloud-based data integration: As more organizations move their data and systems to the cloud, cloud-based data integration solutions will become increasingly important. These solutions will allow organizations to easily integrate and manage data that is stored in multiple cloud-based systems and services.
Real-time data integration: The ability to integrate data in real-time will become increasingly important as organizations look to respond to changing business conditions and customer needs in near-real time. Real-time data integration solutions will enable organizations to quickly and easily access, process, and analyze data as it is generated, providing organizations with the insights they need to make quick, informed decisions.
Increased automation: As data integration becomes more complex and organizations continue to collect and store large amounts of data, automation will become increasingly important. Automated data integration solutions will help organizations reduce the time and resources required to integrate data, increase data quality, and improve data governance.
Machine Learning and AI integration: Machine Learning and AI technologies are becoming increasingly sophisticated, and they will play a bigger role in future data integration. Machine Learning can assist with data validation, cleaning, and mapping, and AI-based algorithms could provide intelligence to the data integration process, allowing it to adapt and learn from past integration experiences.
Big Data Integration: Big Data integration will also play a significant role in the future of data integration. This will become increasingly important as organizations look to integrate and analyze data from sources such as social media, the Internet of Things (IoT) devices, and connected cars
The new age data integration platforms are cloud-based rather than on-premise, web apps rather than desktop software, benefit from robust transformation tools like dbt, and leverage the capacity of data warehouses and data lakes like Snowflake to consolidate more data than ever before. They don’t rely on a particular stack, rather they are vendor or system agnostic and work independently on any of the systems used by the enterprise.
Having dealt with the pain of Integrating data across organizational silos & boundaries, we have architected the product so that it is easy to use and achieves a reduction in the DATA-TO-ACTION timeframe from years and months to days. Enterprises save a tremendous amount of time by eliminating the need to build, integrate & maintain complex data pipelines.
ScikIQ Connect helps you connect with both Structured and Unstructured Sources of Data. Using its out-of-box integration, you can connect to the following:
Data warehousing Products
Databases: RDBMS, Columnar, NO SQL Application Stores: SAP, Sales Force, Oracle etc File System: FTP, SFTP, Drop Boxes, Parquet, ORC, Avro, CSV, Excel
Hadoop Ecosystem : Hive, Impala, HDFS, Hadoop Ecosystem
Real Time Sources – Kafka Confluent
Log based CDC using Debezium
Process Migration – something unique to ScikIQ – If business users, it allows you to capture data using Standard Process Migration Recipes
SCIKIQ combines different data integration design patterns and utilizes active metadata, knowledge graphs, and Machine Learning to augment data integration and data delivery tasks, across all environments, including hybrid and multi-cloud platforms.
In summary, the future of data integration is likely to involve a greater focus on cloud-based solutions, real-time integration, increased automation, Machine learning, and AI integration, and Big Data integration. These technologies will help organizations more effectively integrate and manage their data, turning it into actionable insights that can drive business growth and success.
The benefits of using SCIKIQ are vast, including cost savings, increased efficiency, and improved decision-making capabilities. Don’t miss out on the opportunity to elevate your data management to the next level. Shortlist SCIKIQ as your go-to enterprise data management platform and experience the difference it can make for your organization.
Explore more here
https://www.scikiq.com/blog/scikiq-the-future-of-data-management-is-here/ or check https://scikiq.com/