Manage inputs, processing and outputs for your analytics
inProcess Data Factory is a Data Management Solution for Analytics (DMSA) developed by IPC Global. It catalogs all of your data sources and profiles their contents like tables, columns, views and API objects.
By leveraging manufacturing techniques in data processing, we are able to ensure consistent results. Publishing curated tables into data stores for business intelligence workers results in governed analytics.
Deliver a Data Supply Chain, not a Data Warehouse
Supply Chain Managers enable access to data regardless of the sources. Techniques for just-in-time data, streaming data, semi-structured data, and traditional warehoused data need to be applied. Checking the data for quality as it goes through the process ensures consistency and trust.
Voluminous data is accounted for by leveraging object storage services. Semi-structured data is managed by leveraging tagging and indexing services. Data modeling is based on a network database model, rather than a hierarchical SQL-based model. When the network is viewed as a graph, object types are nodes and relationship types are arcs, with individual nodes often being accessible through multiple arcs, or paths.
Data literacy is predicated on a Data Dictionary
The meaning, aliases and origin of analytic dimensions and measures are fundamental. Governing their meaning and use develops understanding. Data literacy can be a strategic differentiator and facilitate innovation.
Business intelligence developers draw from the Data Dictionary the items they need to produce dashboards, analytics, and reports. Their speed and accuracy are greatly improved when drawing from reusable attributes. Knowing the source and lineage of the data brings context and further meaning to the information being presented.
Bring-your-own analytics
Inevitably data is required by multiple business intelligence, inquiry, reporting, and machine learning platforms. inProcess Data Factory supplies each tool with accurate, complete, and timely data from a governed Data Store. Beginning with Store security, a central service manages row and field-level security all the while monitoring each access request.
Curated data objects can be accessed directly and loaded into virtually any tool. Formulated data models are accessed via ODBC, JDBC or Restful API. Along with the data comes the dictionary and lineage for the developer and end-user of the data alike. Everybody derives value from inProcess Data Factory.
Why we created inProcess Data Factory
The tasks of building a data warehouse, managing master data and checking for data quality, all while developing stored procedures and views requires huge amounts of developer time to be spent on repetitive, non-value added tasks. This leads to high-costs of deployment, reliance on legacy technologies, and all too often- failed projects.
We created inProcess DataFactory to liberate database developers from these repetitive, data-processing tasks and dramatically reduce their report request queue. And when developers are freed from the repetition of data-processing, they can focus on publishing a curated, single source of truth and creating real business value for their users.
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