From a business intelligence perspective, it is critical to go from data to insights as fast as possible. As data analytics leaders say – TTV or time-to-value is a critical metric to track in any data analytics or business intelligence process. But this often becomes a challenge where there are a variety of data sources including databases and data warehouses, cloud/SaaS applications, Excel sheets, and unstructured data from documents.
The key is to figure out a solution that’d process all this data from disparate sources and make it available for data consumers. In short, we need a solution that will unify and normalize the data so it becomes useful.
Denodo enables seamless data integration for complex pipelines through data virtualization solutions, which leverages a logical data fabric for data integration and management. It provides data access to business users in real-time and also makes security and governance easy through the unification of data.
Data Virtualization: A key technology to enable modern data integration
Typically, data integration requires changes to be made at multiple layers. But with data virtualization, rapid integration and change become possible as distributed databases and multiple heterogeneous data stores can be accessed and viewed as a single database. It does not require ETL to be performed on data with transformation engines, but instead, data extract, transform and integration are performed virtually by Data Virtualization servers.
The application does not require technical details on where the data is stored and how it is formatted to retrieve and manipulate data. The second good news is that it does not need heavy infrastructure as the data goes to the customers and not the other way round.
Denodo’s solution for seamless data integration for complex pipelines has the following capabilities:
● Faster Access to Data: This is made possible through Zero Replication, with data remaining in its location and connected to other sources without having to be copied or moved.
● Data Abstraction: Business users need not know where the data resides but can still access it.
● Real-Time Access: Users can access data even as it is updated or changed.
● Agility: A universal semantic layer across multiple consuming applications enables changes to be made to the data without disrupting the business.
● It does not need a large infrastructure.
Denodo Features for Data Integration
Data Virtualization renders the Denodo solution at a low cost and enables cloud-native deployments. Multi-cloud and hybrid-cloud deployment, management, and monitoring are made possible through automated and transparent infrastructure management via a web-based user interface. A newly designed web-based user interface with the SSO option also enables the integration of all tools within the Denodo Platform and all Denodo environments, including a browser-based design studio for enhanced user experience.
A new data science notebook enables advanced analytics and data science workflow management. Complex analytical scenarios can experience exceptional performance through smart query acceleration using Summaries for a logical data warehouse or fabric environments. In-Memory Parallel Processing further accelerates data access with unparalleled speed.
In addition to SQL, REST, and OData options, GraphQL also helps with enhancing data service and API support. Improve data-based decision-making with a suite of automated lifecycle management features that reduces the time needed to manage data, further supported by ML-driven automatic recommendation through a Dynamic Data Catalog.
Denodo Platform Advantage
The Denodo Platform architecture is designed to enable connecting a variety of data sources, integrating them, and making them accessible to different business users in a form best suited to their needs.
The advantages it provides include:
● Integrating and delivering data in real-time with a high-performance data virtualization engine.
● A single sign-on and an intuitive, unified Web UI.
● A data science notebook based on integrated Apache-Zeppelin
● A visual no-code/low-code design studio that is Wizard-driven with auto-suggestions and autocomplete
● Virtual models are created using zero-code to expose data from any source to any user quickly.
● No-code creation of data APIs using GraphQL, REST, OData with OAuth, SAML and Open API support.
● Connectivity to a variety of cloud-based sources such as Amazon Redshift, Azure Synapse Analytics, Google BigQuery, and Databricks Delta; SaaS apps such as Salesforce, Marketo, and Google Analytics; and cloud data stores such as AWS S3, Azure Data Lake Storage, and Google Cloud Storage.
Businesses can seamlessly upgrade to the Denodo Platform for additional data management features such as the machine learning data catalog. This will allow their data integration layer to be expanded into an advanced logical data fabric.
Indium — A Denodo Partner
Denodo’s data virtualization platform combined with Indium Software’s expertise in big data and analytics is a formidable combination that can help businesses derive more value from their data. Indium Software is a two-decade-old software company that provides state-of-the-art, end-to-end professional services on top of the Denodo data virtualization platform, modernizing data landscapes for the digital transformation of daily operations.
The comprehensive set of Denodo services that Indium provides will enable you to leverage your data for optimal results. These include:
● Virtual Data Mart for different functions drawing data from various operational data sources
● Extended DWH by merging data with an operational data source
● Hybrid DWH where a logical data model is created with data in multiple data warehouses
● Virtual Sandbox for Data Modelling enables a real-time view of data across multiple sources in their location
● Self Service BI lets business users explore data using a virtualized layer with necessary data security and governance
● Enterprise Business Data Glossary to harmonize and catalog data at the virtual layer for downstream applications
● Unified Data Governance that lets downstream applications access data with little trace to the physical location of the data
● Virtual master data harmonization using the virtual layer as the master data
● Enterprise Data Services where virtualized data is used as the central gateway for all downstream applications