IBM acquires StreamSets
We are happy to inform that IBM StreamSets for real-time data integration are now generally available.
Leaders must successfully guide organisations and make quick decisions based on up-to-date data in order to stay ahead of the competition and boost their bottom line without impeding growth. In fact, organisations that depend heavily on data are three times more likely than those that don’t to claim meaningful advances in decision-making.
However, getting accurate, current data to support decision-making is extremely difficult for organisations. Eighty-two percent of businesses rely on outdated information when making decisions, and 85 percent of them claim that doing so results in poor choices and lost money. Businesses need a strong data strategy and a solid approach to data integration patterns as they strive to enhance consumer experiences, adopt a more secure stance, and embrace how to expand analytics and AI projects.
Real-time data integration
The issue of stale data is exacerbated by increases in data volume, diversity, and velocity. Organisations need to be able to adapt quickly to the rapid evolution of data since it is a dynamic resource. Ingesting, processing, and writing data as soon as it becomes available is known as real-time data integration. In comparison, batch-style data integration handles data in a sporadic or predetermined manner. By assisting in maintaining continuous data processing, real-time data integration provides a solution to these omnipresent problems.
Data is continually consumed in real time by streaming data pipelines from a variety of sources with different formats and structures. If transformation is required, the data is then loaded to a target system, which might be a data lake, data warehouse, or any other desired location. Streaming data pipelines deliver new data for different use cases in a timely way by continuously integrating data as it becomes available.
Use cases where collecting insights quickly within seconds provides value to the business are those that profit from real-time data integration. Among them are:
- Real-time reporting and analytics: Enables quick insights and data-driven choices by processing and analysing large volumes of data quickly from a variety of sources. This results in actionable intelligence being generated in a matter of seconds.
- Fraud detection: Enables organisations to recognise and respond to any dangers by giving them instant access to a steady stream of carefully selected data from throughout the organisation. It also enables them to respond quickly to suspicious activity.
- Security: Combines cybersecurity platforms with real-time streaming data infrastructure to break down data silos, provide rich contextual information for improved situational awareness, and optimise costs and scalability.
StreamSets IBM
Introducing IBM StreamSets, a software as a service (SaaS) for integrating data in real time across multicloud and hybrid settings
In comparison to mid-2023, major companies will have three times as much unstructured data across their on-premises, edge, and public cloud locations by 2028, predicts Gartner. The data itself is changing over time due to several reasons such modifications in user behaviour, external circumstances, or data gathering techniques, in addition to the formats of the data. Data drift, a phenomenon whereby data distribution shifts over time, can have an adverse effect on the precision of models and systems that depend on stable data patterns, leading to inconsistent outcomes and suboptimal decision-making.
Clients can solve these problems and operationalise real-time data integration by setting up and overseeing intelligent streaming data pipelines to supply the high-quality data required to propel digital transformation, thanks to IBM StreamSets, which are now available. Companies can:
- To reduce data staleness, provide real-time insights, and expedite decision-making processes, establish dependable streaming data pipelines across hybrid cloud systems.
- Use intelligent data pipelines to minimise data drift. Prebuilt drag-and-drop stages that are meant to recognise and adjust to data drift automatically shield pipelines from alterations and unanticipated changes.
- Stream data of any kind from a variety of sources: Build streaming pipelines that adapt to changes in schemas automatically, whether the data is organised, semi-structured, or unstructured.
IBM StreamSets: How to Use Them
Customers may create reusable streaming data pipelines with IBM StreamSets, which are flexible and adaptable, to facilitate quick and accurate decision-making. With the solution, complex data pipelines may be built and implemented without the need for labour-intensive bespoke code thanks to a visual-oriented architecture. In order to increase efficiency at the enterprise level, it provides a range of prebuilt transformations, connectors to several sources and destinations, and a strong software development kit (SDK).
With a SaaS control plane and engines kept apart, IBM StreamSets utilises a hybrid architecture. For secure data processing and decreased data outflow, users can deploy it anywhere their data is stored, be it on-site, in any geo, cloud, or any of the main hyperscalers.
Integration of real-time data and IBM Data Fabric
A modern data fabric design must include data integration as a fundamental element, particularly in light of the increasing volume, velocity, and variety of data that is being generated by increasingly distant sources inside hybrid, multicloud settings of enterprises. Data integration technologies have developed to accommodate a variety of integration approaches due to the fact that data is stored in many locations and formats.
The IBM approach to a data fabric architecture is modular and made up of highly interconnected services because of the particular requirements of businesses and because of certain use cases. Whether they are for artificial intelligence, business intelligence and analytics, or other industry-specific requirements, clients can select from a range of flawlessly integrated data integration technologies that suit their demands.
Leading industry solutions for transporting and transforming mission-critical data with extract, load, and transform (ELT) processing are included in the portfolio, such as IBM DataStage. IBM gives customers a smooth and all-inclusive solution for developing, implementing, and maintaining data pipelines across all data sources and integration patterns with IBM Databand, the observability solution for data pipeline monitoring and issue remediation supporting the whole portfolio. No matter the type of data integration style, clients can handle a broad range of use cases with IBM StreamSets, a crucial addition that enables real-time streaming data pipelines.
At IBM, they are dedicated to developing and inventing to satisfy the demands of their customers. Users can now scale intelligent decision making, analytics, and AI by gaining access to real-time data using IBM StreamSets.
