Enterprise | Process | Data Science

Compute and Store has become a cloud and onsite cost to consider. Enterprises have enterprise processes that produce transaction records. Large database reporting is typically built overtime with plans at the time. Repetitive low-grain queries can cost with Compute and time. Also, if the database is not completely synced on time and "company dimensions" for full Integrated development environment (IDE) multidimensional use, improvements or a new structure can be used.

Orchestrated EDW™ (Sync/Summarize) | EDW²™ (Describe/Square/Project)

Our service and framework can be completely Alexicon code around major applications and data integration tools and/or we work with existing and new services, software and/or cloud solutions to achieve the “Seven Levels of Maturity” for optimal enterprise data performance. We seek and team with best-in-class software and cloud solutions for each level and with integrations.

EDWs are SQL-based and our approach is SQL-based schemas and tables. We do use R and Python with SQL.

The Orchestrated EDW Framework runs a compact enterprise data model. In-memory with drill-to a EDW Massively Parallel Processing (MPP) database for detail and Data Lake for select storage and processing.

Data Science activities

EDW²

Some key EDW² process areas are Ingest, Catalog, Predict, Tune, Score, Compare, Vectors and Numeric Levels. Below is a image showing historical data and the use of Data Science (generates data - red areas are some created with EDW²).

Contact us to learn more.

Enterprise. Orchestrated.

Enterprise Operating System (EOS)

Enterprise Resource Planning (ERP) and surrounding systems: Customer Relationship Management (CRM), Supply Chain Management (SCM), Human Resources Management System (HRMS), Information Technology Service Management (ITSM), other COTS and In-house Built Applications.

Integrated Applications and Analytics.

In-house and Cloud Planning, Migrations and System Operations.

Process focused Work Instructions.

Leverage a Data Dictionary and "Metadata" for the Enterprise to assist with planning software applications and the data landscape.

Enterprise Metadata >

Process

Enterprise Business Processes and Technical Processes for Systems and Data.

Align key processes across the Enterprise to achieve optimal performance. Sync Enterprise Applications and Analytics.

Time intelligence speeds operations and provides clear communication with Associates, Customers, Partners and Suppliers.

Formal Lean Six Sigma or streamlined methods and techniques.

Define, Measure, Analyze, Improve and Control

Statistical Process Control (SPC): Run Charts, Control Charts and Design of Experiments

Gain the process advantage and include learning in the EDW and Data Lake.

Analytics

Enterprise Visualizations, Dashboards and Reports.

Data Science

Leverage Desktop Excel, SQL, R, Python and Scala code. Hyperscale activities.

Integrate Data Science activities in the EDW for Enterprise-wide computations.

Data Mgmt.

Enterprise Applications, Other Data, EDW and Data Lake.

Data Roadmap >

Enterprise Operating System (EOS)

Process

Analytics

Data Science

Data Mgmt.

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