The Client

Mediant Health Resources specializes in providing IT subject matter solutions. Mediant’s focus is on driving value through data to improve performance and clinical outcomes. Mediant offers outstanding strategic consulting, project management, and training for many of the nation’s most widely respected healthcare organizations. Mediant Health Resources strives to improve its client’s software systems by providing exceptional IT consultants to both providers and payers.

Executive Summary

Mediant, since its inception, has conducted its day-to-day business (resource management, payroll, commissions, leave, reporting/dashboarding) using non-cloud-based technologies that made it difficult for users to access it remotely. Recently Mediant invested heavily in building a more robust cloud-based application to manage their business. Through the process of building a new application, most of their analytical capabilities were lost due to back-end structural changes

The Challenge

Excel Reporting

Mediant relied heavily on Excel for reporting and dashboarding, which is not easily scalable, lacks security, is not collaborative, and has become unstable

Outdated Architecture

Due to the outdated architecture, Mediant was seeking a fresh new approach to visualizing data and engaged WCI Consulting to help design and implement a solution.

Cost Effective

Understanding the issues that were needing to be resolved, we needed to be able to implement changes and come up with solutions that would last into the future but in a cost-effective way.

Solution

WCI worked closely with the Mediant team to develop a secure, scalable, and easily accessible financial and commissions application (FCA) in the AWS platform. FCA replaced the existing Excel-based data entry application. Some of the AWS services used to create FCA were RDS Postgres, API gateway, Incognito, Lambda, and Amplify. Utilizing WCI’s experience with creating cloud-based data and analytics platforms, AWS Quicksight was deployed to replace the existing outdated excel based approach. WCI felt this was an easy decision due to the simplicity of embedding visualizations into applications, its low cost compared to other visualization tools, its ability to scale, compatibility across multiple devices, and ease of use. Learn more about other companies that have overcome their business challenges thanks to WCI.

Results and Benefits

Because of the ease of employing AWS services, WCI was able to deliver a robust data and analytics platform quickly and at a lower cost than using traditional on-premises solutions.

This AWS solution allows Mediant Health Resources to securely access the FCA application from wherever they are, on any device, not just when they are in the office. This secure solution also allows for the quick adding of new users and the removal of users who are no longer entitled to access the data. Due to the scalability and stability of the platform, Mediant has increased efficiency in its interactions with FCA.

The old excel based data entry methods have been replaced with a responsive application that allows data to be entered in a fraction of the time. Processes that used to take hours have been reduced to minutes. In addition to improving the data entry process, Mediant can now view all analytical content directly in the FCA application using embedded Quicksight visualizations.

With Quicksight, the speed of developing visual content has significantly increased thanks to its ease of connecting to sources, creating content, and deploying that content. As a result, Mediant can deliver enhancements and expand its offerings at a much faster pace than they could on their previous platform.

Aws Quicksight Visualization

See what more WCI clients have to say about our services.

5 Steps To Designing An Enterprise-Ready Data Warehouse In Aws At Wci Consulting

The right approach to an enterprise-ready data warehouse architecture is fundamental to your organization. If you want to become data-enabled, start a data-driven transformation program or grow your organization using data, data warehousing modeling, consulting, and business intelligence tools can be a massive asset to your business.

Today, we’re sharing a deep dive into some core components you need to build a successful enterprise-ready data warehouse in AWS.

What is an enterprise data warehouse?

An enterprise data warehouse (EDW) is a large, centralized data repository that supports an organization’s reporting and analysis needs. It is built to integrate data from multiple sources and to provide a single version of the truth for the entire organization.

An EDW typically has scalability, performance, data integration, quality, governance, security, accessibility, and flexibility. Large organizations often use these data warehouses to handle large amounts of data and support complex reporting and analysis requirements.

What are the benefits of using a data warehouse?

  1. Informed decision-making: Data warehouses provide a single version of the truth, making it easier to understand and analyze the data, which leads to better business decisions.
  2. Centralized data storage: A data warehouse allows you to store all your organization’s data in a single, centralized operational database, making it easier to manage and access.
  3. Improved data quality: Data warehousing analytics tools and techniques can be used to clean, transform, and standardize data, improving the overall quality of the data.
  4. Increased data accessibility: Data warehouses make it easy for business users and business analysts to access and analyze data, regardless of where it is stored or in what format it is in.
  5. Better performance: Data warehouses are optimized for reading and querying large amounts of data to handle complex queries and large data sets more efficiently than traditional databases.
  6. Scalability: With a data warehouse, it is possible to scale up as the amount of data grows, to ensure continued performance and accessibility.
  7. Cost-effective: Data warehousing solutions like Amazon Redshift allow a pay-as-you-go pricing model, which helps organizations be cost-effective and eliminates the need for upfront investments for hardware and software.

Can you build an enterprise data warehouse in AWS?

Yes. It is possible to build an enterprise data warehouse in AWS using various services such as Amazon Redshift, Amazon RDS, and Amazon S3. Amazon Redshift is a fully managed data warehouse service that can handle petabyte-scale data warehousing and big data analytics workloads. 

Amazon RDS can be used to set up a relational database as the data source for the data warehouse, while Amazon S3 can be used to store and retrieve data for the data warehouse. Additionally, AWS Glue and AWS Lake Formation can be used for data cataloging and ETL processes.

What is the data warehouse tool offered by AWS?

AWS offers a data warehouse tool called Amazon Redshift. It is a fully managed, petabyte-scale data warehouse service in the cloud that allows users to quickly set up, operate, and scale a data warehouse that is highly available and durable, with a pay-as-you-go pricing model. 

Amazon Redshift is designed to integrate with other AWS services, such as Amazon S3, Amazon EMR, and Amazon QuickSight, making it easy to load, query, and analyze data in your data warehouse. Additionally, it supports a variety of data warehousing and big data analytics use cases, including reporting, analytics, data warehousing, and business intelligence.

What are the key steps to designing a data warehouse?

Setting up data warehouse models with business analysts like WCI can be fast and straightforward. 

Step 1: Determine Core Business requirements and sources: This is the first and most crucial step in designing a data warehouse. It involves identifying the key business requirements and objectives that the data warehouse is expected to support. This step also includes identifying the data sources used to populate the data warehouse. These sources include transactional systems, external data feeds, and other data warehouses.

Step 2: Collect and Analyze the Information: This step involves collecting data from the identified sources and analyzing it to understand the data structure, relationships, and quality. Data profiling and data discovery tools can be used to understand the data better and identify any issues that need to be addressed.

Step 3: Identify Core Business Processes: This step involves identifying the core business processes that the data warehouse will support, such as reporting, analytics, and data mining. This will help determine the required data elements and the type of data that must be stored in the data warehouse.

Step 4: Design and Construct a Data Layer: This step involves designing the logical and physical data models for the data warehouse. This includes determining the appropriate data structures, relationships, and storage methodologies. This step also involves creating the necessary database schemas, tables, and views to support the data warehouse.

Step 5: Plan Data Movement and Transformations: This step involves planning how data will be moved from the source systems to the data warehouse and how it will be transformed to meet the requirements of the data warehouse. This includes designing the extract, transform, and load (ETL) processes and creating the necessary mappings, workflows, and jobs to support the data movement and transformations.

Getting The Most from Your Data

To get the most out of using a data warehouse, it is essential to define precise business requirements, collect and analyze data from various sources, identify core business processes, design and construct a data layer that meets those requirements, and plan data movement and transformations. It is also essential to have a well-designed and well-implemented data governance plan that includes data quality, security, and compliance. 

You also need a skilled team with experience in data warehousing, data modeling, ETL, and data analysis to ensure that the data warehouse is properly designed, implemented, and maintained. Regular monitoring and performance tuning are also essential to ensure that the data warehouse runs efficiently and effectively. 

If you’re ready for effective enterprise planning, connect with the experts at WCI today

Learn about cloud migration services to AWS at WCI

Amazon Web Services (AWS)

Watch this space for more of WCI’s AWS tutorials.

Beyond the AWS Tutorials

If you’re stuck and need help in all things Amazon Web Services or Microsoft Power BI, you’ve come to the right place. WCI has been in the business of getting data to decision makers since 1998 so we really know our stuff. Check out our AWS Consulting or Power BI Consulting pages for more information.

Also, if you have any suggestions for a tutorial video give us a shout on the contact us page to share your thoughts, we’re always looking for new ideas!

Power BI to RDS MySQL Connection on AWS

Are you looking to connect Microsoft Power BI to an AWS (Amazon Web Services) RDS (Amazon Relational Database Service) instance?

This video shows you how to connect Power BI to a MySql AWS RDS instance from the Power BI Desktop system. Amazon Relational Database Service (Amazon RDS) makes it easy to set up, operate, and scale a relational database in the cloud. It provides cost-efficient and resizable capacity while automating time-consuming administration tasks such as hardware provisioning, database setup, patching and backups.

Need To Go Beyond the AWS Tutorials?

If you’re stuck and need help in all things Amazon Web Services you’ve come to the right place. WCI has been in the business of getting data to decision makers since 1998 so we really know our stuff. Check out our AWS Consulting page or Power BI Consulting page for more information.

Also, if you have any suggestions for a tutorial video give us a shout on the contact us page to share your thoughts, we’re always looking for new ideas!

Power BI to SQL Server Connection on AWS

Are you looking to connect Microsoft Power BI to SQL Server on an AWS (Amazon Web Services) RDS (Amazon Relational Database Service) instance?

This video shows you how to connect to a Microsoft SQL Server AWS RDS instance from the Power BI Desktop. Amazon Relational Database Service (Amazon RDS) makes it easy to set up, operate, and scale a relational database in the cloud. It provides cost-efficient and resizable capacity while automating time-consuming administration tasks such as hardware provisioning, database setup, patching and backups.

Beyond the AWS Tutorials

If you’re stuck and need help in all things Amazon Web Services you’ve come to the right place. WCI has been in the business of getting data to decision makers since 1998 so we really know our stuff. Check out our AWS Consulting page for more information.

Also, if you have any suggestions for a tutorial video give us a shout on the contact us page to share your thoughts, we’re always looking for new ideas!

>>> Check out our video tutorial on connecting Microsoft Power BI to a PostgreSQL Amazon RDS (Amazon Relational Database)

Power BI to PostgreSQL Connection on AWS

Are you looking to connect Microsoft Power BI to a PostgreSQL AWS (Amazon Web Services) RDS (Amazon Relational Database Service) instance?

This video shows you how to connect to a PostgreSQL AWS RDS instance from the Power BI Desktop. Amazon Relational Database Service (Amazon RDS) makes it easy to set up, operate, and scale a relational database in the cloud. It provides cost-efficient and resizable capacity while automating time-consuming administration tasks such as hardware provisioning, database setup, patching and backups.

Beyond the AWS Tutorials

If you’re stuck and need help in all things Amazon Web Services you’ve come to the right place. WCI has been in the business of getting data to decision makers since 1998 so we really know our stuff. Check out our AWS Consulting page for more information.

Also, if you have any suggestions for a tutorial video give us a shout on the contact us page to share your thoughts, we’re always looking for new ideas!

>>> Check out our video tutorial on connecting Microsoft Power BI to SQL Server on Amazon RDS (Amazon Relational Database)

Tableau to SQL Server Connection on AWS

Are you looking to connect Tableau to an AWS (Amazon Web Services) RDS (Amazon Relational Database Service) instance?

This video shows you how to connect to a PostgreSQL AWS RDS instance from the Tableau Desktop. Amazon Relational Database Service (Amazon RDS) makes it easy to set up, operate, and scale a relational database in the cloud. It provides cost-efficient and resizable capacity while automating time-consuming administration tasks such as hardware provisioning, database setup, patching and backups.

Beyond the AWS Tutorials

If you’re stuck and need help in all things Amazon Web Services you’ve come to the right place. WCI has been in the business of getting data to decision makers since 1998 so we really know our stuff. Check out our AWS Consulting page for more information.

Also, if you have any suggestions for a tutorial video give us a shout on the contact us page to share your thoughts, we’re always looking for new ideas!

Enable Rapid Innovation with DevOps


Organizations using a DevOps model deliver applications quicker and innovate faster. AWS offers elastic, on-demand infrastructure resources and tooling designed to support continuous integration and delivery, infrastructure as code, microservices, and monitoring & logging. With AWS, there’s no hardware to setup, manage, or operate, allowing you to focus on addressing customer needs. This flexible model allows your organization to scale as your needs grow and only pay for what you use.

Devops-Top-Ban

 

Why Choose AWS for DevOps?


Each AWS service is ready to use if you have an AWS account. There is no setup required or software to install.


Provision one or thousands of server instances and scale capacity up or down within minutes automatically. Easily configure these resources at scale to meet changing workload demands.


You have the option to use AWS via the AWS Command Line Interface or through APIs and SDKs. You can also model and provision AWS resources and your entire AWS infrastructure using declarative AWS CloudFormation templates.

AWS helps you use automation so you can build faster and more efficiently. Using AWS services, you can automate manual tasks or processes such as deployments, development & test workflows, container management, and configuration management.


Use AWS Identity and Access Management (IAM) to set user permissions and policies. This gives you granular control over who can access your resources and how they access those resources.


AWS supports a large ecosystem of partners that integrates and extends AWS services. Use your preferred third-party and open source tools with AWS to build an end-to-end solution.

DevOps on AWS


DevOps is the combination of cultural philosophies, practices,and tools that increases an organization’s ability to deliver applications and services at high velocity: evolving and improving products at a faster pace than organizations using traditional software development and infrastructure management processes. This speed enables organizations to better serve their customers and compete more effectively in the market.

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