Enterprise. Orchestrated.

Cloud Providers

Contracts & Workload Management

AWS, Azure, GCP, IBM and Oracle are top U.S. cloud providers. These are "hyperscaler" clouds with AWS, Azure and Google currently being the largest. They provide legacy Information technology (IT) services that scale and newer serverless solutions. Major uses are Virtual Machines (VMs) and Hyperscale for large data processing. Multi-cloud use is also increasing (both compute and storage). Selecting and optimizing IT services internally and among clouds is key. Dell VxRail/VMWare Horizon hyper converged infrastructure (HCI) systems are now gaining popularity for In-house Clouds. Our expertise and technical abilities provide business and IT assistance for in-house and cloud services. Many Enterprise software applications are moving to the cloud, as well as, Enterprise Data Warehouses (EDWs).

For cloud services, determining aggregate spend, service performance and proactively making service changes can be a challenge to manage. Also, making a choice to build in-house, cloud on-premise or in-the-cloud.

Workload Management

  • Manual and automated workloads
    • Applications, Installs, Updates, Monitoring, VMs, Containers, ETL, SQL and serverless use
  • System prototype testing (reliability, speed and use)
  • Price Plans
  • Price Cost Analysis
  • Reserved Services (plan ahead)
  • Portability Testing (switching a service or provider)
  • Label or ID Services for reporting
  • Allocate Services to departments or organizations
  • Monitor supplier Service recommendations
  • Optimize Services and spend continuously
    • Adjust, add or remove service

Multi-cloud use

Avoid unexpected high bills when using cloud services by planning, budgeting, allocating, monitoring and optimizing performance and spend. Proactive self-management. Change services when needed.

Microsoft, Google, Amazon Web Services and IBM are leaders in Gartner's 2021 Magic Quadrant for Cloud AI Developer Services


Below are systems that provide a service. Servers can be added physically or virtually to scale (cloud advantage). Commodity servers are used in cloud data centers to reduce hardware costs.

Enterprise Data

Most companies are moving rapidly toward improved application integration, reporting and working on their enterprise data warehouses (EDWs). Visualizations, dashboards and reports “report” data. They all require a grid(s) or chunk-like datasets (smaller the better). Advanced data modeling is a highly-valuable area (a Company’s association model). It is where all the pieces come together for an enterprise data model with fully-managed master data.

The better the enterprise data model, the fewer applications, visualizations, dashboards and reports (consolidation and standardization). We have worked in environments where tens of thousands of reports exist because of natural EDW growth (adding data sources, dimensions and facts). Evolves overtime.

Accelerated help

Your advantage with Alexicon assisting is 23 years of experience with strategic data models. We mentioned a few years back the connection with multidimensional data models and high-dimensional statics. A fully integrated EDW provides a Company’s Multidimensional Data Model to perform Multi-dimensional Statistics. It has all possible dimensions and facts needed to perform data science computations. A structured data warehouse can drill from the top to needed levels quickly and with accuracy. The same drilling is needed for High-dimensional statistics and other data science computations. For EDWs, users should never experience inaccuracy (1 + 1 = 2.01) when using a system.

Enterprise. Orchestrated.


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.


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)



Data Science

Data Mgmt.