Intelligent Middleware

EntityStream is pioneering the Intelligent Data Stream
Realtime flows that renovate and improve your data

Traditional digital platforms can be costly and burdensome.  

Entitystream offers a data platform designed to help you execute meaningful decisions quickly—without the burdensome expense or complex coding requirements. You’ll gain access to our suite of technolgy that redefine how your data works for you. 

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DISPARATE DATA SOURCES LAYER

Whether your data sources are comprehensive CRM and ERP systems, or siloed spreadsheets that lack version control and consistency, our platform ingests all your information to provide connectivity across your organization. Our platform can input any type of data, from any type of source.

DATA CLEANSING LAYER

In the data cleansing layer, information is purged and updated to fit a desired perspective based on your relevant business priorities. Previously siloed pieces of information will be connected allowing users to see all relevant information under a pertinent lens such as sales, financials, productivity, and more.

DIMENSIONAL LAYER

Data hubs are quickly replacing the old model of data warehouses, lakes, and graveyards. In our Dimensional Rollup Layer, we organize information in an automated realtime cube. Use of our Dimensional Layer allows you to traverse freely through your data, rather than being bound by the inflexible structure in which it is stored.

SEMI-STRUCTURED COLLECTION LAYER

Rather than storing data in a traditonal relational way we organize data starting with a framework based on how you think about your business, rather than a framework dictated by the rigid constraints of your data sources.

DE-DUPLICATION LAYER

Much of your data will suffer from duplicates, whether that is customer, supplier, employee, part, product or asset. The de-duplication layer uses the semantic layer in the product to enable us to identify technical duplicates across a wide variety and format of sources.

CONCEPTUAL LAYER

Many data sources will have wildly different data structures, this can lead to it being difficult to visualize across those data sources, either in a single view of customer or to be able to reconcile and aggregate financial data. The conceptual layer helps you to bridge this data gap.