Discovery Hub: Actionable insights with access to the data you need

Discovery Hub®

– enabling

self-service

BI & Analytics

You use some of the most popular and innovative data visualization tools currently available — tools such as Power BI, Tableau and Qlik. Since you love data, you know there is plenty of it to analyze from an ever-increasing number of sources. Power BI, Tableau and Qlik give you stunning visualizations.

With the endless possibilities to visualize data in tools such as Power BI, Tableau and Qlik, you want to tweak data in different directions. You want to access more data sources too, maybe with the help of IT but mostly without having to wait for them or the assistance of external consultants.

When different users access data sources in different ways, you see data quality issues emerge, resulting in conflicting reports. You and your colleagues end up with silos of extractions and transformations.

“Easier, Better & Faster Analytics
Through Automation”

Discovery Hub® is a comprehensive end-to-end solution that lets you easily merge data from a wide variety of data sources into a single version of the truth. It also allows automation to model data so that line of business users can easily understand the data.

At the same time, data is properly defined so that all users of reports and analytics speak the same language. For example, if revenue is defined to include tax, then this definition will be used throughout the organization, without misunderstanding.

By combining this platform with your choice of visualization tools, you have the full power of business intelligence (BI). By using Discovery Hub® as the solid foundation for your analytics setup, you create a scalable, structured, governed and secure environment that lies within a compliant, self-service analytics framework, allowing you to practice near real-time analysis on large sets of data.

Using Discovery Hub®, business users, BI and IT developers can collaborate on an agile, fully integrated information platform that supports iterative workflows to quickly create reports and dashboards. This lets business leaders make quality business decisions without impacting the core systems of the business

Discovery Hub® by TimeXtender helps customers gain more business
value and greater data insights by:

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Easily integrating and accessing an organization’s growing number of data sources

 

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Easily integrating and accessing an organization’s growing number of data sources

 

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Avoiding reporting errors due to changes in data sources or server environment

 

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Adding consistency to reports and KPIs created through well-governed and validated data

 

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Reducing external consultancy costs and reliance on in-house IT

 

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Enhancing scalability, so Power BI, Tableau or Qlik can be rolled out enterprise-wide

 

Cloud, On-Premises and hybrid

At TimeXtender, we’re keen to help customers and partners as they move towards a cloud-based Discovery Hub®. We realize the pace and terms of cloud transformation will be different within each organization. With this in mind, we work towards a pure cloud solution while continuing to offer an onpremises as well as hybrid solution to suit all needs.

With the TimeXtender model, you can select the data you want to deploy on-premises or in the cloud to address your specific operational requirements. With this approach, you can gradually evolve to a full cloud deployment.

If you built your on-premises analytics solution in Discovery Hub®, it’s easy to move to the cloud. There is no need to manually migrate data schemas, metadata, users and data — just indicate the Azure cloud server and Discovery Hub® will do the rest.

Here’s how it works

The Discovery Hub® has four levels: Front ends, Semantic Layer,
Modern Data Warehouse and the Operational Data Exchange

Front ends — Helping Business Users,
Data Scientists and Data Analysts

All types of analytics tools can connect to Discovery Hub®. Data scientists and analysts may want to connect statistical or predictive analysis tools such as R, Python, Alteryx or SPSS to the ODX to access raw data.

Other business users, such as financial controllers, marketing analysts and sales officers, may need to connect AI, machine learning, performance management analytics or visualization tools directly to the modern data warehouse in order to uncover greater insights.

For decision makers who use Power BI, Tableau or Qlik, it is easy to access the data in Discovery Hub® by automating the connection to the semantic layer.

Shared Semantic Layer: One Version of the Truth for Power BI, Tableau, Qlik

With the shared semantic layer, governed models are defined once then automatically used to deliver data in the right form and context to Power BI, Tableau and Qlik. The view is based on a single version of the truth, where everyone works with the same definitions and values. 

The shared semantic layer allows mapping from the Modern Data Warehouse (MDW) to a business context model that meets the needs of a specific business unit — organizational, geographical, etc — or analytical purpose.

Regardless of visualization tool, users will arrive at the same figures, avoiding conflicting reports. The shared semantic layer is also part of future-proofing your organization, with the ability to easily switch between multiple visualization tools, avoiding the need to build models from scratch.

Modern Data Warehouse (MDW): Understanding and Trust

The Modern Data Warehouse is built on the notion that business users need to access and understand data. In order to be useful, data must be available in a format that business users can understand. Unlike traditional data warehouse approaches, no judgments are made about what data is relevant, since the goal is to support selfservice.

In the MDW, data is improved, enriched and consolidated. With the MDW, data quality issues need be handled only once. Golden records are created in which similar data from different systems can be combined into one data set. The MDW also manages to preserve historical data, since data changes over time and source systems are sunsetted.

The MDW solves another part of the challenges to achieve true self-service analytics — all challenges related to accessing meaningful and trustworthy data.

Operational Data Exchange (ODX): Access to all Data of Likely Value

The ODX solves all challenges related to data access, which is half of the challenge to achieving true self-service analytics. Users of visualization tools avoid direct data access without needing IT, while IT can stay responsible for maintaining the ODX. Business users with domain knowledge, such as BI specialists, can concentrate on data modeling and delivering self-service analytics to data scientists, data analysts and users of visualizations tools that use data in the other layers — the Modern Data Warehouse (MDW) and semantic layer.

The strength in this approach is the ability to connect to the ever-growing and ever-changing number of data sources.

It’s all about automation

Discovery Hub® is powered by TimeXtender’s revolutionary software. This software helps
close the data to insight gap by automating all that can be automated in the data discovery
life-cycle. With Discovery Hub®, you can accelerate data on-boarding, keep track of all your data, and auto-generate documentation that helps with
regulatory compliance, i.e. GDPR.

Works faster and better with the Discovery Hub® from TimeXtender

Seeing is believing

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