WhereScape is thrilled to invite you to...
WhereScape Partners with Data Vault Inventor Dan Linstedt
| July 9, 2016
Linstedt is the world’s leading authority on all things Data Vault and will prove to be an invaluable resource to the Company as we build out our Data Vault automation development solutions. The integration and synergy between the Data Vault 2.0 methodology and WhereScape’s automation solutions enable organizations to deliver analytical results in hours and days instead of weeks and months while lowering risk and reducing costs.
“What attracted me to WhereScape is its ease of use, automation and code generation capabilities, and the growing number of organizations around the world that are successfully using WhereScape for Data Vault development,” Linstedt said in a press release issued today at WhereScape’s briefing to the Boulder BI Brain Trust (BBBT), a consortium of industry analysts, experts, and practitioners from around the world founded by Claudia Imhoff.
WhereScape will deliver automated Data Vault 2.0 development solutions based on Linstedt’s methodology and best practices and consistent with his vision and requirements. In turn, Linstedt will advise WhereScape on our Data Vault initiatives and regularly meet with WhereScape’s R&D team to provide feedback on WhereScape’s customer-driven Data Vault development activities.
The biggest winner in all of this is our customers who are successfully using WhereScape RED to develop data warehouses and business intelligence (BI) systems based on the Data Vault 2.0 data model. Data Vault modeling is attractive as it provides long-term historical storage of data coming in from multiple operational systems. It is also a method of looking at historical data that deals with issues such as auditing, tracing of data, loading speed and resilience to change.
Group Health successfully used WhereScape RED and Data Vault 2.0 to develop a fully documented Enrollment and Membership subject area for its new data warehouse with complete data lineage, governance and Teradata best practices. “Group Health now has a very clean environment and architecture with WhereScape RED and the Data Vault data model,” said Rhonda Ogilvie, Enterprise Data Warehouse Manager for Group Health. To read more about Group Health’s experiences with WhereScape and Data Vault, read the case study.
And stay tuned as we leverage our new partnership to further cement our status as the go-to vendor for automating Data Vault development.
What Makes A Really Great Data Model: Essential Criteria And Best Practices
By 2025, over 75% of data models will integrate AI—transforming the way businesses operate. But here's the catch: only those with robust, well-designed data models will reap the benefits. Is your data model ready for the AI revolution?Understanding what makes a great...
Guide to Data Quality: Ensuring Accuracy and Consistency in Your Organization
Why Data Quality Matters Data is only as useful as it is accurate and complete. No matter how many analysis models and data review routines you put into place, your organization can’t truly make data-driven decisions without accurate, relevant, complete, and...
Common Data Quality Challenges and How to Overcome Them
The Importance of Maintaining Data Quality Improving data quality is a top priority for many forward-thinking organizations, and for good reason. Any company making decisions based on data should also invest time and resources into ensuring high data quality. Data...
What is a Cloud Data Warehouse?
As organizations increasingly turn to data-driven decision-making, the demand for cloud data warehouses continues to rise. The cloud data warehouse market is projected to grow significantly, reaching $10.42 billion by 2026 with a compound annual growth rate (CAGR) of...
Developers’ Best Friend: WhereScape Saves Countless Hours
Development teams often struggle with an imbalance between building new features and maintaining existing code. According to studies, up to 75% of a developer's time is spent debugging and fixing code, much of it due to manual processes. This results in 620 million...
Mastering Data Vault Modeling: Architecture, Best Practices, and Essential Tools
What is Data Vault Modeling? To effectively manage large-scale and complex data environments, many data teams turn to Data Vault modeling. This technique provides a highly scalable and flexible architecture that can easily adapt to the growing and changing needs of an...
Scaling Data Warehouses in Education: Strategies for Managing Growing Data Demand
Approximately 74% of educational leaders report that data-driven decision-making enhances institutional performance and helps achieve academic goals. [1] Pinpointing effective data management strategies in education can make a profound impact on learning...
Future-Proofing Manufacturing IT with WhereScape: Driving Efficiency and Innovation
Manufacturing IT strives to conserve resources and add efficiency through the strategic use of data and technology solutions. Toward that end, manufacturing IT teams can drive efficiency and innovation by selecting top tools for data-driven manufacturing and...
The Competitive Advantages of WhereScape
After nearly a quarter-century in the data automation field, WhereScape has established itself as a leader by offering unparalleled capabilities that surpass its competitors. Today we’ll dive into the advantages of WhereScape and highlight why it is the premier data...
Data Management In Healthcare: Streamlining Operations for Improved Care
Appropriate and efficient data management in healthcare plays a large role in staff bandwidth, patient experience, and health outcomes. Healthcare teams require access to patient records and treatment history in order to properly perform their jobs. Operationally,...
Related Content
What Makes A Really Great Data Model: Essential Criteria And Best Practices
By 2025, over 75% of data models will integrate AI—transforming the way businesses operate. But here's the catch: only those with robust, well-designed data models will reap the benefits. Is your data model ready for the AI revolution?Understanding what makes a great...
Guide to Data Quality: Ensuring Accuracy and Consistency in Your Organization
Why Data Quality Matters Data is only as useful as it is accurate and complete. No matter how many analysis models and data review routines you put into place, your organization can’t truly make data-driven decisions without accurate, relevant, complete, and...
Common Data Quality Challenges and How to Overcome Them
The Importance of Maintaining Data Quality Improving data quality is a top priority for many forward-thinking organizations, and for good reason. Any company making decisions based on data should also invest time and resources into ensuring high data quality. Data...
What Makes A Really Great Data Model: Essential Criteria And Best Practices
By 2025, over 75% of data models will integrate AI—transforming the way businesses operate. But here's the catch: only those with robust, well-designed data models will reap the benefits. Is your data model ready for the AI revolution?Understanding what makes a great...
Guide to Data Quality: Ensuring Accuracy and Consistency in Your Organization
Why Data Quality Matters Data is only as useful as it is accurate and complete. No matter how many analysis models and data review routines you put into place, your organization can’t truly make data-driven decisions without accurate, relevant, complete, and...
Common Data Quality Challenges and How to Overcome Them
The Importance of Maintaining Data Quality Improving data quality is a top priority for many forward-thinking organizations, and for good reason. Any company making decisions based on data should also invest time and resources into ensuring high data quality. Data...
What is a Cloud Data Warehouse?
A cloud data warehouse is an advanced database service managed and hosted over the internet.