Masterdata partner, MANTA, releases Manta SaaS, empowering customers with unparalleled code-level data lineage within a hosted cloud environment. With Release 42, Manta responds to evolving customer requirements, offering comprehensive solutions adaptable to both on-premises and cloud settings. This update delivers intuitive automation, expanded customization, and amplified value for data engineers, architects, analysts, and business users.
Data lineage, a critical safeguard for data quality, identifies and tracks data changes and potential flow disruptions, effectively preventing long-term issues that affect data trust. Release 42 elevates this by enhancing user experience, streamlining automated processes, and fortifying intelligence capabilities, thereby optimizing workflows and offering prescriptive insights. Moreover, it broadens platform compatibility, including robust code-level scanning capabilities for Databricks.
Manta SaaS: Unmatched Cloud Flexibility with Complete Functionality
Customers now have the choice between an on-premises Manta experience or the new Manta SaaS, enjoying the same robust platform in a fully hosted cloud environment. The Manta SaaS solution offers enhanced flexibility, catering to a wider array of businesses, aligning with distinct use cases and requirements, thereby reducing overall ownership costs.
Intuitive Automation & Versatile Connectivity
Manta's Release 42 unlocks myriad possibilities for organizations to extract maximum value from their data lineage through automation-driven intelligence, augmented connectivity options, and system-level visualizations:
- Automated Cross-System Lineage Mapping: Identifies connections between systems within a data landscape, minimizing the need for manual lineage stitching by data stewards and engineers.
- Deduced Lineage: Illuminates system interactions, providing a comprehensive high-level lineage overview without exhaustive source scanning.
Databricks UC Scanner:
Expands lineage insights by scanning the Databricks environment, integrating and analyzing data from diverse sources. This integration is pivotal for leveraging Databricks' ML/AI capabilities effectively.
Bridges the technical-business divide by visualizing top-level applications, systems, and integrations, crafting an overarching architectural map to showcase repository systems and interactions.
These updated features foster stronger technical and business alignment, presenting a comprehensive data lineage view that provides valuable insights for all stakeholders.
"Manta's latest cloud capabilities, advanced customization, and top-tier visualizations make the platform more agile than ever," said Gary Allemann, MD of Master Data Management. "This release reflects MANTA's commitment to meeting evolving customer needs with value, irrespective of where they are in their data lineage journey."
OpenManta Enables End-to-End Lineage
OpenManta Designer offers a user-friendly graphical interface (GUI) for creating lineage, complementing Manta's scanners. To streamline end-to-end lineage implementation, OpenManta Designer facilitates faster integration of custom assets. Moreover, it enables manual data lineage creation through a drag-and-drop interface or spreadsheet, empowering users to establish connections between related items effortlessly.
For comprehensive information on Manta's Release 42, visit manta.io.
Drexel University award recognizes data integrity leader, Precisely, for building a culture of trusted data - powered by their own market-leading solutions
Master Data Management partner, Precisely, has been recognised as an Analytics 50 honoree by Drexel University's LeBow College of Business. This accolade commends the innovative application of their own data integrity solutions amid a period of significant digital transformation, marked by substantial growth and merger and acquisition (M&A) endeavours.
Under the leadership of forward-thinking Chief Data and Information Officer, Amy O'Connor, the project team successfully instilled a culture of data integrity across all facets of the organization. In just nine months, Precisely seamlessly migrated 228 datasets across eight lines of business, implementing robust data standardization processes for sustained data consistency. This effort led to an impressive 98% improvement in data quality.
Diana Jones, Executive Director of the Center for Business Analytics at LeBow, noted, "With our latest research showing that 70% of organizations with low levels of trust in their data point to data quality as the biggest challenge to making confident decisions, it’s remarkable to see the speed and scale at which Precisely were able to overcome their data challenges by relying on their own solutions."
The Drexel LeBow Analytics 50 is a prestigious national recognition program that honours organizations at the forefront of analytics-driven problem-solving. Honorees are selected by a panel of researchers and practitioners who evaluate nominations based on the complexity of the business challenge, the analytics solution implemented, and the solution’s business impact on the organization. These honorees effectively bridge academia and industry, showcase best practices, and demonstrate the profound impact of data-driven strategies on their businesses.
“We’re very pleased to be able to showcase this example of data integrity innovation through our Drexel LeBow Analytics 50 program," concludes Jones.
Amy O'Connor emphasized Precisely's commitment to data integrity: "As the global leader in data integrity we have a responsibility to demonstrate best practice in achieving trusted data. Whether it’s our own business or one of our 12,000 customers worldwide, we’re proud to power organisations with the accurate, consistent, and contextual data needed to make confident decisions and
In the pursuit of confident business decisions, customers now have access to interoperable data integrity services offered by Precisely, the global frontrunner in data integrity solutions. These services operate seamlessly in any data environment, be it on-premises or in the cloud.
Master Data Management partner, Precisely, has announced the latest innovations within the Precisely Data Integrity Suite. Customers can now swiftly construct data pipelines, seamlessly integrate data into new cloud platforms using an extensive range of connectors and effortlessly utilise enhanced features such as data observability, geocoding, and data enrichment capabilities. The suite's unified data catalogue facilitates seamless interoperability among its services and introduces a new user interface that enables users to search and explore an extensive inventory of business and technical metadata.
Sanjeev Mohan, Principal and Founder at SanjMo and former Gartner Research VP, commented, "Today’s businesses wrestle with delivering trusted data from hybrid environments to analytic systems using a mix of point solutions. They lose control of their data as it moves from data producer to data consumer, and as a result, data issues aren’t identified until they hit downstream systems."
Organizations are under increasing pressure to rapidly leverage the power of reliable data for confident decision-making while simultaneously reducing costs by maximizing efficiency. A recent study conducted by the Center for Business Analytics at Drexel University's LeBow College of Business reveals that data-driven decision-making is the foremost objective for organizations worldwide, with 77% of business leaders identifying it as their main priority for 2023. This is closely followed by the positive business impacts associated with confident decision-making, including operational efficiency (73%), cost reduction (62%), revenue generation (59%), and regulatory compliance (57%).
The suite's interoperable services enable customers to make informed business decisions based on reliable data. These services allow proactive issue detection, provide a comprehensive understanding of data usage and lineage, enable data enrichment through curated datasets, and make data accessible wherever it is most needed, whether that's in an on-premises, cloud, or hybrid environment.
Key enhancements to the Data Integrity Suite include:
New Data Quality service: Precisely's market-leading data quality capabilities, which are already favoured by customers, are now directly available within the suite. Customers can design data quality pipelines using an intuitive interface and execute quality processes natively in the cloud or any other data environment. Critical data can be easily validated, geocoded, and enriched to ensure accuracy, consistency, and contextual relevance for downstream operations and analytics.
Integrated data catalogue: Metadata is automatically captured through any connection in the Data Integrity Suite, driving a user experience centred around a data catalogue. Users can access a complete inventory of business and technical metadata, enabling effortless searching, exploration, comprehension, and collaboration across critical data assets.
Support for hundreds of new connectors: The suite now offers expanded compatibility with a wide array of data environments, allowing seamless integration of data into new platforms using numerous additional connectors. The Data Integration service within the suite facilitates real-time data replication from diverse sources, including complex mainframe IMS and VSAM sources, as well as leading cloud platforms such as Snowflake, Google BigQuery, and Amazon Web Services (AWS) Redshift. This ensures that data is available precisely where it is needed most.
Convenient access to geocoding and data enrichment: Address data can be easily validated, geocoded, and prepared for enrichment by assigning a unique and persistent PreciselyID. This functionality is accessible through the suite's new cloud-native Geocode API or the Data Quality service.
New data observability capabilities: The Data Observability service within the suite now enables proactive monitoring of additional data attributes, allowing the detection of issues before they impact downstream systems. Organizations benefit from alerts on schema drift, significance thresholds, and comprehensive support for all major cloud data warehouses. These features provide greater insight and control over data observations than ever before.
Gary Allemann, MD at Master Data Management, said, "The Data Integrity Suite now combines Precisely's long-standing expertise in data quality with data observability and data governance, empowering teams to not only observe, detect, and predict problems but also to rectify them in the very environments where the data resides."
Designing and Implementing Analytics Data Architecture is a new business intelligence course designed to address modern data management challenges and provide insights into modern practices and data architecture design patterns and extends both our BIe and data architecture curriculums.
In today's rapidly evolving business world, utilizing data and analytics has become imperative for organizations to compete effectively. However, with the ever-advancing technologies and capabilities, it is challenging for businesses to keep up with the changes and manage data for maximum impact. Despite this, most organizations still cling to the outdated data architecture of the BI era, which is insufficient for supporting modern analytics use cases. Merely patching new components onto the surface of legacy architecture is not sustainable and fails to provide adequate support for modern data requirements.
Although modern data architecture may seem complex and difficult to implement, it is crucial to step up and embrace it. The first step is to define the necessary business and data capabilities, followed by integrating new capabilities into the existing data management practices.
The step-by-step approach outlined in the course ensures that businesses can establish a sustainable and adaptable data management architecture that caters to their present and future needs. By taking this course, businesses can gain a competitive edge in the market and achieve maximum value from their data resources.
You will learn:
- The reasons that legacy data architectures need to be modernized
- The multitude of requirements for effective analytics data management
- The similarities and differences of Data Lake, Data Fabric, and Data Mesh architectures
- Techniques to identify analytics business capabilities and requirements
- Techniques to identify analytics data capabilities and requirements
- How to apply architectural design patterns and frameworks
- How to adapt reference architectures
- The path from requirements to a well-designed architecture
- Six techniques for architecture implementation
This course is geared towards:
- Practicing and aspiring data architects
- CDOs, CIOs, and other executives responsible to provide data management leadership
- Enterprise, analytics, and technology architects who work with data architects
- Data engineers and systems engineers
- Designers and developers of data management and analytics systems
- Anyone who needs to collaborate with data architects
The course is developed and delivered by elearningCurve Education Director, Dave Wells and Daniels College of Business lecturer Jed Summerton, and will contribute towards a Certified Information Management Professional (CIMP) accreditation in Data Architecture or the CIMP in Business Analytics.
Use Safyr to liberate your SAP MDG metadata for data governance, data catalogue, master data management and other data projects.
Master Data Management partner, Silwood Technology Limited has announced the availability of Safyr® for SAP MDG metadata harvesting. SAP’s Master Data Governance (MDG) application supports customers who need to combine master data from a number of sources and then manage it effectively.
This release of Safyr adds yet further support for customers who need to incorporate metadata from SAP’s array of complex ERP applications with enterprise data transformation programs. Safyr is the leading ERP metadata harvesting, visualization and discovery software product designed specifically for use by data analysts, data architects and data scientists.
Customers use Safyr to exploit the data structures in SAP MDG systems. This is a critical task for accelerating the effective delivery of a wide range of information-led projects such as data catalogues, data governance, data warehouse, data analytics, master data management, and more.
Technically, SAP MDG uses a Data Model paradigm to define the data structures that are to be the subject of its Master Data Governance features. Safyr liberates the metadata for these data models by harvesting the SAP MDG tables that define these models. Safyr is particularly valuable if the customer has significantly extended the set of standard SAP MDG data models or has multiple instances to manage.
Gary Allemann, MD at Master Data Management, said, "The trend towards a composite business architecture means that more and more organisations are seeking to access data within SAP and make it available to external analytics and governance platforms, like Data360. This addition to Safyr makes it easier to access SAP MDG data and is well timed."
Safyr for SAP MDG is delivered as part of Silwood’s Safyr for SAP ERP product at no extra cost. It is available immediately to all Safyr for SAP customers who have an existing subscription or are current on support and maintenance.
About Silwood Technology Limited
Silwood Technology is the leading supplier of self-service metadata harvesting software products for Enterprise Application Packages including SAP, SAP BW, SAP S/4HANA, SAP MDG, SAP SuccessFactors HXM, Salesforce, PeopleSoft, JD Edwards, Siebel, Oracle E-Business Suite, and Microsoft Dynamics.
Silwood Technology’s product, Safyr® supports customers and partners who need to accelerate the delivery of complex data governance and other critical data and information management transformation projects.
Sample customers include BASF, ATB Financial, Hewlett Packard, VW, Twitter, Henny Penny, Aldi, Centrica and many others in virtually all vertical sectors.
Silwood partners include Collibra, Alation, Informatica, Quest Erwin, Zeenea, Solidatus, Idera and more