Cloud Providers

Contracts & Workload Management

AWS, Azure, GCP, IBM and Oracle are top U.S. cloud providers. These are "hyperscaler" clouds with AWS and Azure currently being the largest. They provide legacy Information technology (IT) services that scale and newer serverless solutions. Multi-cloud use is also increasing (both storage and compute). Selecting and optimizing IT services internally and among clouds is key. Our expertise and technical abilities provide business and IT assistance for internal, internal cloud and in-the-cloud services.

For cloud services, determining aggerate 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


Technology is the sum of techniques, skills, methods, and processes used in the production of goods or services or in the accomplishment of objectives, such as scientific investigation. - Wikipedia

Alexicon - areas to consider when analyzing and designing a single application or "service." Column on the left is your Company.


Shareowners (Share Price and Total Shareholder Return (TSR)


Short and Long term Objectives

Mission and Vision


Products and Services

Strategic advantage(s)

Key Performance Indicators (KPIs)

Master Data Management and Transations

Targets and Results

Performance: Revenue, COGS, Expenses, Quality and Value


Talents and Skills


Requirements, design, implementation and training

Understands and furthers processes

Helps design and define processes, systems, KPIs, indicators and reporting

Provides process and system training

Indicators and metrics

Goals and Targets


Makes decisions

Change Management

Continuously improves processes


Define, Measure, Analyze, Improve and Control

How things get accomplished

Embedded in systems, analytics and work instructions

System model and transformation process

Standardized process versus work-arounds (avoids two or more processes for same area)

Manual, Simi-automated and Automated

Dollars, counts and time durations

Guides consistent quantity and quality output


Internal and/or External

Users like the system

Meets the business process

Flexible for process improvements

Fosters involvement and use

Ability to transition to newer tools, methods and techniques

Avoids work-arounds

Highlights issues

Embeds business processes and workflows

Area analytics

Cost savings

Return on investment (ROI)

Where will the service reside?


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. The system in the middle is in-house and managed by a cloud partner.

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 20 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 intergraded 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.

With data models (data) associated well, IT spends most of their time building needed applications and analytics (avoids point-solutions, workarounds, duplication and unsureness). Main mission is to ensure accuracy, functionality, security and fast click times for users. Most systems are available or online 24/7. IT also needs to coordinate with all parts of the Company and with Suppliers across many systems.