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Resources

Literature about our products and deployments.

White papers

Why the Data Warehouse is dead

Warehouse failings for modern data and uses; Overcoming challenges with the Fusion Hub





  • Version: 1.0
  • Release: May, 2018
  • Authors: Datanova Scientific LLC

Organizations need data to show their 'big-picture' to drive analytics, efficiency, & compliance. A common solution for this is the data warehouse. However, warehouses are past their heyday by over 20 years, and they consistently fail for modern data.

We introduce the Datanova Fusion Hub as a superior replacement for warehouses. The Fusion Hub has succeeded where warehouses fell short in U.S. national intelligence, banks, and other domains.

We compare the Fusion Hub with warehouses on four dimensions – cost, performance, analytics-support, and flexibility.

Unsurprisingly, the Fusion Hub wins on all four dimensions. What is surprising is the large margin by which warehouses have fallen behind.


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Case Studies

Data Unifier Vs. coding

Key findings: Data Unifier saved 91% effort over Python coding





  • Version: 1.0
  • Release: May, 2018
  • Authors: Datanova Scientific LLC

Many organizations use custom code to perform their data integration. This invariably ends up being a more expensive and brittle undertaking than initially planned.

In this experiment, we measured the time taken to add a new data source by Python coding vs. the Fusion Hub. We used a Zillow real estate dataset, which we fused to some existing bank data.

Two engineers with advanced degrees in Mathematics went head-to-head (it was intense). The first used Python with a variety of open libraries. The other used Fusion Hub tools and process.

Fusion Hub won by a landslide. Not only did Fusion Hub take a fraction of the time to add the new data source, it was also did more with the data. For example, it converted some tabular data to time-series, a task that was tedious in Python.


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Data Unifier Vs. data integration tool

Key findings: Data Unifier saved almost 80% effort over a traditional data integration tool





  • Version: 1.0
  • Release: May, 2018
  • Authors: Datanova Scientific LLC

Traditional data integration is time consuming and expensive. We set out to quantify this experience in this experiment.

We redid and enterprise-grade integration task. It was previously implemented in a big-name-company data integration tool (...name withheld). We redid the task in the Fusion Hub.

The Data Unifier only took a small percentage of the time taken with the other tool. The final configuration was much more compact and understandable.

Also, the output of the Data Unifier was passed to the Fusion Hub, yielding a previously missing capability in with ease.


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Product Sheets

Data unifier product sheet






  • Version: 1.0
  • Release: May, 2018
  • Authors: Datanova Scientific LLC

Product sheet for the Data Unifier.


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Fusion Hub product sheet






  • Version: 1.0
  • Release: May, 2018
  • Authors: Datanova Scientific LLC

Product sheet for the Fusion Hub.


We respect your privacy. We will never share your email with anyone or spam you.


Industry briefs

Fusion Hub for healthcare






  • Version: 1.0
  • Release: May, 2018
  • Authors: Datanova Scientific LLC

Despite their immense promise, healthcare data are difficult to use for clinical research. Various addressable factors impede the research process, such as lack of data standardization across platforms, research being conducted in individual silos, and loss of data fidelity due to compliance-driven anonymization.

These problems have been previously encountered in other domains such as U.S. National Intelligence. Datanova Scientific has ported some of these solutions and lessons learned in other domains to healthcare informatics through the Datanova Fusion Hub.


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BKP for data-driven knowledge






  • Version: 1.0
  • Release: May, 2018
  • Authors: Datanova Scientific LLC

Data is a substrate of knowledge. Exploiting enterprise data streams provides unobtrusive and 'always-current' knowledge capture. As a converse benefit, enterprise data activities are empowered by being connected to knowledge.

In this brief, we discuss how the Big Knowledge Platform (BKP) creates a sustainable continuum between data and knowledge. Operationalizing knowledge in this way can provide immediate and impactful ROI. We will provide examples of how we have achieved this for government clients.


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