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Building a scalable Data Platform?

Whether you're implementing Data Vault 2.1 or modernizing your analytics architecture, our experts help you turn complex data challenges into practical, future-proof solutions. From hands-on implementation to in-depth training, we support your team every step of the way.

In Data Vault Friday

Data Vault on Databricks

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In our ongoing Data Vault Friday series, our CEO Michael Olschimke addresses a pertinent question raised by the audience, unraveling the discourse around the compatibility of Data Vault 2.0 (DV2.0) with Databricks.

“There has been hype going on on LinkedIn about whether or not DV2.0 is suited to exist on Databricks. Many people disagree that it is. The most significant comments are ‘lots of joins,’ ‘performance getting data out,’ and ‘not suited for modern automation.’ The latter ties to tools creating generated code per object VS. parameterized pipelines.”

In this illuminating video, Michael delves into the discussions surrounding the suitability of Data Vault 2.0 in the Databricks environment. He provides insights into the concerns raised, such as the perceived challenges related to joint operations, data retrieval performance, and the alignment with modern automation practices.

Michael offers a balanced perspective, exploring the nuances of utilizing DV2.0 on Databricks and addressing the key considerations raised in the LinkedIn discussions.

Meet the Speaker

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Michael Olschimke

Michael has more than 15 years of experience in Information Technology. During the last eight years he has specialized in Business Intelligence topics such as OLAP, Dimensional Modelling, and Data Mining. Challenge him with your questions!

In Beginner, Salesforce

Warum Eigentlich Salesforce?

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Warum Eigentlich Salesforce?

In diesem Webinar geht es um die Frage “Warum eigentlich Salesforce?”. Wir werden uns die 3 Hauptvorteile des CRM-Systems von Salesforce ansehen: Integrierbarkeit, Erweiterbarkeit und Anpassbarkeit. Erfahren Sie, wie Salesforce Ihnen dabei helfen kann, Ihr Unternehmen zu transformieren und Ihre digitalen Prozesse zu optimieren.

Sie werden verstehen, wie Salesforce Ihre Arbeitsabläufe nahtlos integrieren und automatisieren kann, um Ihnen Zeit und Ressourcen zu sparen. Wir zeigen Ihnen, wie einfach und schnell es ist, Salesforce zu erweitern und anzupassen, um den spezifischen Bedürfnissen Ihres Unternehmens gerecht zu werden.

Melden Sie sich jetzt an und erfahren Sie, warum Salesforce die beste Wahl für die digitale Transformation Ihres Unternehmens ist.

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Webinar Agenda

1. CRM Systeme in der digitalen Transformation → Shared Customer Insight (nach Jeanne Ross)
2. Warum Salesforce so gut passt. (Salesforce order MS Dynamics in Spitzengruppe)
3. Grund 1 Integrierbarkeit
4. Grund 2 Erweiterbarkeit
5. Grund 3 Anpassbarkeit

Meet the Speaker

Picture of Markus Lewandowski

Markus Lewandowski

Markus Lewandowski hat mehr als 6 Jahre Salesforce Erfahrung und ist ein zertifizierter Salesforce Berater bei Scalefree. Er hilft Kunden in ganz Europa, Salesforce Umgebungen zu implementieren, zu verbessern und in ihren Tech-Stack zu integrieren.

In Data Vault Friday

Multi-temporal Source Data (Sap Hrms) in Data Vault

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In our ongoing Data Vault Friday series, our CEO Michael Olschimke explores a valuable question from the audience, shedding light on the intricacies of modeling an SAP HRMS source with SCD type 2 data and dealing with time-dependent information in Data Vault 2.0.

“Could you please guide us on how to model an SAP HRMS Source that holds the data in SCD type 2 in the source itself with an effectivity start date and end date for each change? What will be the best way to deal with time-dependent data in Data Vault 2.0?”

In this enlightening video, Michael provides practical guidance on modeling strategies for incorporating SAP HRMS source data with Slowly Changing Dimension (SCD) type 2 attributes directly in the source. He addresses the complexities of handling time-dependent data within the Data Vault 2.0 framework, offering insights into the best practices for managing effectivity start and end dates for each change.

Michael shares valuable considerations and recommendations, providing a clear roadmap for efficiently handling time-dependent data scenarios in Data Vault 2.0 projects.

Meet the Speaker

Profile picture of Michael Olschimke

Michael Olschimke

Michael has more than 15 years of experience in Information Technology. During the last eight years he has specialized in Business Intelligence topics such as OLAP, Dimensional Modelling, and Data Mining. Challenge him with your questions!

In Data Vault Friday

EDW Environments in Data Vault

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In our ongoing Data Vault Friday series, our CEO Michael Olschimke addresses a crucial question from the audience that highlights a common challenge in data projects.

“I’m currently working on a project where the ‘environments’ (Dev, Prod, Test) are not well administrated. This topic is not mentioned at all in the DV2.0 methodology. Could you please elaborate on the roles of these environments and how to correctly use and manage them? As context, the problem faced at the moment by the company is that they’re not being able to test correctly and then implement. Also, the environments don’t necessarily count with the same information.”

In this insightful video, Michael provides a comprehensive discussion on the roles and importance of environments (Development, Production, Test) in the context of Data Vault 2.0 methodology. He addresses the challenges faced by the company, emphasizing the critical role that well-administered environments play in testing, implementing, and ensuring data consistency across different stages.

Michael shares practical insights into the correct utilization and management of environments, offering guidance on establishing a robust environment strategy within the Data Vault framework.

Meet the Speaker

Profile picture of Michael Olschimke

Michael Olschimke

Michael has more than 15 years of experience in Information Technology. During the last eight years he has specialized in Business Intelligence topics such as OLAP, Dimensional Modelling, and Data Mining. Challenge him with your questions!

In Intermediate

Automating Business Logic

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Automating Business Logic

In this webinar, you’ll learn that Data Vault automation is not restricted to loading data, but can also be applied to the presentation layer.

There’s always some repeatable business logic – think of calculations such as currency conversion, Lifetime Value (LTV), or Net Present Value (NPV) – to feed different reports, even if all of them contain different information.

We’ll explain how you can create custom business templates and add additional layers in the information marts, to apply calculations repeatedly and even interdependently, thereby extending the scope of Data Vault automation from integration to presentation.

This webinar focuses on practical solutions.

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Webinar Agenda

1. How to get data out of a Data Vault.
2. What’s a PIT, what’s a bridge?
3. What’s meant by virtualization?
4. How to identify low-hanging fruits, i.e. the repeatable business logic in your solution.
5. How to automate those business rules using VaultSpeed.

Meet the Speakers

Profile picture of Michael Olschimke

Michael Olschimke

Michael has more than 15 years of experience in Information Technology. During the last eight years he has specialized in Business Intelligence topics such as OLAP, Dimensional Modelling, and Data Mining. Challenge him with your questions!

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Jonas De Keuster

Jonasis VP Product Marketing at VaultSpeed. He had close to 10 years of experience as a DWH consultant in various industries like banking, insurance, healthcare, and HR services, before joining the company. This background allows him to help understand current customer needs and engage in conversations with members of the data industry

In Data Vault Friday

Data Vault 2.0 Source System Disaster Recovery

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In our ongoing Data Vault Friday series, our CEO Michael Olschimke engages with a challenging question from our audience, aiming to find an elegant solution to a complex scenario.

“I’m trying to find an elegant way of addressing the following problem.

You have a DV2.0 Insert Only BI deployment fed by multiple OLTP systems. One of these OLTP systems will be subject to a disaster and associated recovery process. This will be done with a loss of 3h worth of data from the OLTP in question. During the 3 hours, multiple loads into the DV were completed.

I’m trying to avoid an effectivity satellite for each hub.”

In this insightful video, Michael explores strategies for handling data from multiple source systems with disaster considerations in a Data Vault 2.0 Insert Only BI deployment. The question prompts a discussion on avoiding the use of an effectivity satellite for each hub, offering alternative approaches to address the challenges posed by data loss during disaster recovery.

Michael shares practical insights and considerations for designing resilient solutions within the Data Vault framework while optimizing the balance between complexity and efficiency.

Meet the Speaker

Profile picture of Michael Olschimke

Michael Olschimke

Michael has more than 15 years of experience in Information Technology. During the last eight years he has specialized in Business Intelligence topics such as OLAP, Dimensional Modelling, and Data Mining. Challenge him with your questions!

In Data Vault Friday

Data Vault 2.0 Project Tracking

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In our continuous Data Vault Friday series, our CEO Michael Olschimke addresses a pertinent question from our audience regarding the application of Scrum in Data Vault 2.0.

“We are struggling with the application of Scrum in Data Vault 2.0: the Kanban board is overloaded with technical user stories. However, in theory, the user stories should be oriented towards the business and user needs.”

In this insightful video, Michael delves into the challenges faced when integrating Scrum methodologies into Data Vault 2.0 projects, particularly the issue of an overloaded Kanban board with technical user stories. The question prompts a discussion on the alignment of user stories with business and user needs, emphasizing the importance of maintaining a business-centric focus.

Michael shares practical insights and recommendations for optimizing the use of Kanban boards in Data Vault 2.0 projects, ensuring a balance between technical requirements and business-oriented user stories.

Meet the Speaker

Profile picture of Michael Olschimke

Michael Olschimke

Michael has more than 15 years of experience in Information Technology. During the last eight years he has specialized in Business Intelligence topics such as OLAP, Dimensional Modelling, and Data Mining. Challenge him with your questions!

In Data Tools, Intermediate

Bring Your Data Vault Automation to the Next Level with DataVault4coalesce

SALESFORCE SOLUTIONS

Data Vault Automation with DataVault4coalesce

A cooperation created DataVault4coalesce, an open source extension package for coalesce.io. In a previous webinar, we explored coalesce.io, a new competitor in the highly contested market of data warehouse automation tools.

coalesce

Level up your Data Vault automation – with DataVault4coalesce

Coalesce is a modern, column-aware data warehouse automation tool. In this webinar, you will learn how Scalefree’s latest publication brings best practices out of the Data Vault world into your coalesce.io experience. This includes data loading patterns, data vault related features, and more! All embedded into easy-to-use UI options to make use of Coalesce’s unique configurable user interface. Tune in to see DataVault4coalesce in action!

Watch Webinar Part 1Watch Webinar Part 2

In this article:

And everyone who watched that webinar might remember that at the end, we announced an even closer relationship between coalesce.io and Scalefree and a commitment to bring Scalefree’s best practices into coalesce.io!

For those who didn’t watch the webinar, you can find it here.

Recap: What is Coalesce?

coalesce.io is a Data Transformation solution made for Snowflake. When working with Coalescse, you build directed acyclic graphs (DAG) which contain nodes. A node represents any physical database object, like tables or views, or even stages and external tables.

Coalesce itself is built around metadata that stores table and column-level information, which describes the structure inside your data warehouse. This metadata-focused design enables a couple of features that strongly drive towards scalability and manageability. 

All the metadata allows a team to track past, current, and desired states of the data warehouse by deeply integrating it and all the workflows that it brings. Additionally, users can define standardized patterns and templates on column- and table-level.

How can Data Vault jump in here?

These mentioned templates open up the gate to implement Data Vault 2.0 related patterns and best practices. Especially on the table level, it might quickly come to mind that you could try to build a template for a Hub or a Link.

On column level, this could be a repeated transformation which is then managed in only one so-called macro, which makes it very easy to implement changes with low to zero impact. You could think of hash key calculation or virtual load-end-dating here.

And that is exactly what we at Scalefree have done since the webinar last year. Lead developers from coalesce.io sat together with Data Vault experts and developers from Scalefree with one goal: Create something amazing that helps users to automate their Data Vault 2.0 implementation!

Datavault4Coalesce

How fast can I build a Data Vault? Yes!

This cooperation created DataVault4coalesce, an open-source extension package for coalesce.io, which will be available on March 16th! Let’s have a sneak peek at a selection of what users can do with DataVault4coalesce.

The first release of DataVault4coalesce will feature a basic set of Data Vault 2.0 entities:

While providing DDL and DML templates for the entity types mentioned above, DataVault4coalesce makes use of Coalesce’s ability to define the UI for each node type. For stages, this means that users can decide if they want DataVault4coalesce to generate ghost records automatically or not, as shown in the screenshot below:

Datavault4Coalesce

This Data Vault related interface can be found across all node types and allows users to adjust DataVault4coalesce to fit their requirements conveniently!

Conclusion

First of all a bummer, DataVault4coalesce will only be available starting from the 16th of March. But there is no reason to wait that long to dive into coalesce.io itself! Since it is now part of Snowflake Partner Connect, it’s never been easier to get your hands on a fresh coalesce.io environment!

Just sign up for a free Snowflake trial here and initialize your coalesce.io experience within seconds by accessing the Partner Connect portal! Then, you just have to load any desired data into it, and you can start building your data pipelines with coalesce.io. And when the 16th of March finally arrives, you just have to add DataVault4coalesce to your coalesce.io environment – and now you can start to build Data Vault faster than ever!

Also, don’t miss out on this recording, where we will show you DataVault4coalesce in action. Watch it here!

– Tim Kirschke (Scalefree)

In Data Vault Friday

(Logical) Information Marts in Data Vault

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In our continuous Data Vault Friday series, our CEO Michael Olschimke addresses a question from our audience that delves into the intricacies of the CDVP2 training.

“We are having trouble understanding the attached slide 28 of the CDVP2 training.

– What is the difference between Business DV Pits & Bridges and Pits & Bridges?
– We are confused about why Business Vault and Info Mart are put into one logical wrapper. Why does physical and logical wrapper differentiate?”

In this elucidating video, Michael provides clarification on the distinctions between “raw” and “business” Point-in-Time (PIT) and bridge tables. The question prompts a discussion on understanding the nuances of these components within the Data Vault methodology.

Michael shares insights into the reasoning behind grouping Business Vault and Info Mart into one logical wrapper while emphasizing the differentiation between physical and logical wrappers. The discussion provides valuable context for participants seeking clarity on the CDVP2 training material.

Meet the Speaker

Profile picture of Michael Olschimke

Michael Olschimke

Michael has more than 15 years of experience in Information Technology. During the last eight years he has specialized in Business Intelligence topics such as OLAP, Dimensional Modelling, and Data Mining. Challenge him with your questions!

In Data Vault Friday

Supersetting in Data Vault

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In our ongoing Data Vault Friday series, our CEO Michael Olschimke engages with a thoughtful inquiry from our audience.

“Dear Scalefree team, we receive data from the source for multiple company forms (like HoldingCompany, JointVenture), and we want to know if it’s recommended to save them in different entities (e.g., HoldingCompany_h/s, JointVenture_h/s) or one big entity (Company_h/s).

If we split them, we will have for each company form (e.g., Holding Company) about 10 links; If we store everything in one Company entity, we may face the situation that different company forms have different master data in the future, besides, it violates the Data Vault 2.0 rule that we should save the data as delivered by the source.”

In this insightful video, Michael delves into the strategic considerations of applying sub-setting and super-setting in the context of Data Vault 2.0. The question prompts a discussion on where to employ these techniques and the potential exceptions that might arise from the default strategy.

Michael provides practical insights and recommendations for effectively handling diverse company forms within the Data Vault framework, ensuring compliance with Data Vault 2.0 principles while addressing the complexities of master data variations.

Meet the Speaker

Profile picture of Michael Olschimke

Michael Olschimke

Michael has more than 15 years of experience in Information Technology. During the last eight years he has specialized in Business Intelligence topics such as OLAP, Dimensional Modelling, and Data Mining. Challenge him with your questions!

In Data Vault Friday

Reference Table Vs. Reference Hub in Data Vault

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In this week’s Data Vault Friday, our CEO Michael Olschimke addresses an intriguing question from our audience regarding the difference between a Reference Table and a Reference Hub.

“If I need to historize the reference table, I can use the Satellite pattern. Ok, I have now a Reference Satellite table. But what about the Reference Hub table? Is it effective to create a table with just one column?”

In this informative video, Michael explores the concept of historizing reference tables within Scalefree‘s Data Vault 2.0 projects. The question specifically focuses on the efficiency and effectiveness of creating a Reference Hub table with just one column.

Michael shares insights into the considerations and scenarios where creating a Reference Hub table with a single column can be a viable and effective approach. The discussion provides practical guidance for handling reference tables within the Data Vault 2.0 methodology.

Meet the Speaker

Profile picture of Michael Olschimke

Michael Olschimke

Michael has more than 15 years of experience in Information Technology. During the last eight years he has specialized in Business Intelligence topics such as OLAP, Dimensional Modelling, and Data Mining. Challenge him with your questions!

In Data Vault Friday

Calculating Hash Keys in Business Vault

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In our ongoing Data Vault Friday series, our CEO Michael Olschimke delves into a thought-provoking question from our audience.

“When calculating hash_key in links in Business Vault, it sometimes can be quite expensive to join all hubs to get the business keys, etc. In many cases, we keep those hash_keys to keep the standards only. And even for any case where you may need to build a satellite for that link, that means you would have the same granularity. So is it still a no-go to generate the link hash_key from the hub hash_keys to prevent expensive joins in some cases? If so, what do you suggest?”

In this insightful video, Michael addresses the considerations and challenges related to calculating hash keys in links within the Business Vault. The question prompts a discussion on the trade-offs between keeping hash keys for standards and the potential expense of joins, especially when dealing with multiple hubs.

Michael shares his expertise on hashing practices in Data Vault 2.0 links, offering recommendations and considerations to optimize the balance between standards and performance in the Business Vault.

Meet the Speaker

Profile picture of Michael Olschimke

Michael Olschimke

Michael has more than 15 years of experience in Information Technology. During the last eight years he has specialized in Business Intelligence topics such as OLAP, Dimensional Modelling, and Data Mining. Challenge him with your questions!

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