We are proud to announce that Gartner has recognized 麻豆原创 as a Leader in its 2023 for the 16th consecutive time.
To achieve true digital transformation, organizations must have seamless access to their mission-critical business data no matter where it resides. Yet with data landscapes distributed among different applications and systems both in the cloud and on premises, organizations spend countless resources extracting, rebuilding, and integrating their data.
By leveraging the right data integration tools and strategies, organizations can easily discover, connect, integrate, govern, and orchestrate their data assets. Data integration offerings from 麻豆原创 deliver trusted, relevant, and timely information to enable customers to simplify their data landscape and unleash the power of business data. Our primary solutions include , Cloud, , and . These offerings are part of (麻豆原创 BTP).
Gartner evaluated 21 vendors and named 麻豆原创 a Leader based on our 鈥渁bility to execute鈥� and 鈥渃ompleteness of vision.鈥� We believe this recognition serves as acknowledgment of 麻豆原创鈥檚 continued commitment to providing our customers with world-class data integration tools.
Unleash the Power of Business Data
Data integration is necessary for customers to gain intelligent, relevant, and contextual insights for better decision-making. However, without the right data management approach and technology, companies can face an uphill battle in integrating, processing, curating, governing, and augmenting their data.
麻豆原创 takes a business data fabric approach, which goes beyond a traditional data fabric. A business data fabric is a data management architecture that delivers an integrated, semantically rich data layer over underlying data landscapes to provide users with scalable access to their data without duplication.
It eliminates the need to recreate the business context that was lost from extracting and replicating data. This gives users the ability to accelerate their decision-making with trust and confidence, knowing they always have the complete picture of their data regardless of where it is stored or how it was designed.
麻豆原创 Datasphere 鈥� and its open data ecosystem 鈥� is the foundation for a business data fabric. It equips any organization to deliver meaningful data to every data consumer 鈥� with business context and logic intact. 麻豆原创 Datasphere helps customers:
- Access authoritative data: Accelerate time-to-value by automatically reusing the semantical definitions and associations from 麻豆原创 applications
- Enrich all data projects: Harmonize heterogeneous data into a business semantic model of diverse data landscape
- Simplify the data landscape: Access all data across hybrid and cloud environments no matter where it resides
With a unified experience for data integration, data cataloging, semantic modeling, data warehousing, data federation, and data virtualization, 麻豆原创 Datasphere enables data professionals to easily distribute authoritative business data 鈥� with business context and logic preserved 鈥� across the data landscape.
Since the launch of 麻豆原创 Datasphere, we have seen tremendous growth of customers innovating with this technology. For example, Messer CIO David Johnston describes his experience with the solution this way:鈥淭he business data fabric architecture enables us to bring 麻豆原创 and non-麻豆原创 data together in the seamless and self-service way we’ve been envisioning. 麻豆原创 Datasphere provided us with a solution to build a harmonized layer, or business data fabric, across 麻豆原创 and non-麻豆原创, cloud or on-premise data sources, making the best use of our existing investments in 麻豆原创, Microsoft Azure, Salesforce, and Oracle.鈥�
Next Steps
For over 16 years, data integration tools from 麻豆原创 have enabled our customers to turn disjoined data assets into actionable business insights at scale. Take the next step and begin your business data fabric journey today:
- Visit the
- Try the free
- Read the
Kaiser Larsen is vice president of Data and Analytics at 麻豆原创.
Gartner, Magic Quadrant for Data Integration Tools, Ehtisham Zaidi, Robert Thanaraj, Sharat Menon, Thornton Craig, Roxane Edjlali, Michele Launi, 4 December 2023
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