AWS and One Six Solutions

As an Amazon Web Services (AWS) partner, we help architect, develop and deliver software and data solutions in the cloud. Our AWS certified Architects and Developers, have the skills needed to help you unlock the power of AWS's cloud platform.

We leverage exclusive partner benefits like the innovation sandbox and AWS credits for POC’s, to help make your project a success.

Software Engineering with AWS

Whether you need to optimize your current AWS architecture or you're new to AWS, we can help you unlock the full power of AWS and the cloud for your business.

Using EC2, Lambda, SNS and DynamoDb we can work with your team to rapidly create scaleable, fault tolerant and highly available applications in the cloud, that are specifically designed to meet your needs.

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Data Engineering with AWS

We empower businesses by maximizing the value they get from their data through AWS.

By leveraging Amazon Redshift, Amazon RDS and Amazon Aurora, we create high performance data and analytics solutions to enable strategic decision making.

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Examples of our AWS work include...

Entertainment Retailer's Analytics Platform

A 2X performance improvement for analytical queries supporting inventory and marketing analytics in the cloud.

Entertainment

Data Lakes and Warehouses

Entertainment Retailer's Analytics Platform

What was the problem?

The retailer’s Strategy and Analytics teams were experiencing run times ranging from hours to days for queries against the largest data sources on their existing data warehouse, negatively impacting the teams’ turn times for new analyses.

How we helped?

One Six Solutions worked with the retailer’s teams to prioritize problem data sources to be ported into Amazon Redshift, and to gather requirements for content and structural changes to those sources in their new environment.  We implemented the data loads for those sources into Redshift.  One Six Solutions converted Tableau workbooks that the teams had been running against the existing SQL Server Data Warehouse environment to the new Redshift platform.

What were some of the tools used?

Data loads were implemented using SSIS, extracting data from SQL Server then using the ZappySys suite of extensions to interface to Amazon S3 / Redshift.  Tableau workbooks were rebuilt and tested in Tableau 10.5.  The new workbooks’ data sources were a mix of extracts (using Hyper) and live query as appropriate, taking advantage of Amazon Redshift’s processing power for aggregate queries.

What were the results?

Queries from the rebuilt Tableau workbooks showed performance improvements of 1 – 2 orders of magnitude compared with the prior versions sourced against SQL Server.  The retailer’s highest-volume data sources (in the 10’s of billions of records) are now available on Amazon Redshift for general use by the Strategy and Analytics teams.

Global Consulting Firm's Pricing And Sales Application

A truly global pricing and sales platform leverages the scalability and elasticity of the cloud.

Consulting Services

Cloud Native Development

Global Consulting Firm's Pricing And Sales Application

What was the problem?

The internal organization of a global consulting firm asked us to help architect and build an AWS solution to price and visualize sales and financial data. Components of the pricing application needed to be moved from a legacy implementation to their more current AWS Pub/Sub architecture. As part of the architecture goals they wanted to consolidate and share internal data, while reducing dependencies with other internal applications. During the course of the project they also wanted to view aggregated pricing data across organizational boundaries.

How we helped?

We helped architect and build various pieces of the pricing application’s orchestration including micro-services for instances of the deal, results of the pricing calculation, reference data lookups and various user interfaces. We also re-architected and moved parts of the application from their legacy implementation to the current architecture (including existing application data) while the application was actively being used in production. We architected and delivered on a pricing implementation that grouped and consolidated pricing data across the company.

What were some of the tools used?

The micro-services application was built using AWS Lambdas with most of the data being stored in Amazon’s Dynamo DB. The various micro-services were decoupled from each other and communicated through publishing SNS notifications. The user interface applications were built using Kotlin, .NET, Angular 2 and Node.js while being hosted in Elastic Beanstalk.

What were the results?

The application is currently being piloted with various groups to improve pricing accuracy and visibility; more groups and users are being added quarterly providing much better insight into global sales and pricing information.

National Autobody Retail Chain’s Analytics Platform

A cloud based analytics environment for a national auto-body retail chain enables compliance reporting and employee training measurement.

Automotive

Data Analytics

National Autobody Retail Chain’s Analytics Platform

What was the problem?

Our client is one of the largest autobody and mechanical repair shops in the nation.  Their retail stores and regional managers were in need of a consolidated reporting and analytics platforms to better understand overall corporate performance, compliance adherence and training programs for their technicians.

How we helped?

The One Six team assisted the client with defining the set of KPIs across each level in the corporate hierarchy.  We worked with the CTO and COO to standardize measurement criteria so they can evaluate their performance against insurance carrier standards for the services they provide.  Interactive dashboards and reports were built allowing for on-demand analysis.

What were some of the tools used?

The Data Warehouse was built in the cloud using Snowflake as the underlying database technology operating in an AWS cloud. Tableau Desktop and Tableau Online were leveraged to create compelling data visualizations to support corporate leadership, regional and retail managers in their decision making.

What were the results?

All levels of the management team down to an individual retail location were now able to consistently view their teams performance and quickly identify areas where action was required.  Compliance reporting with respect to insurance carrier metrics was available online in an easy to use dashboard with the capability to drill into as much detail as required. Corporate training was also able to leverage the reporting to identify what training programs needed to be completed and by which employees.

Global Professional Services Organization's Sales Dashboard

Sub-second response times and instant financial calculations leveraging the cloud.

Consulting Services

Application Modernization

Global Professional Services Organization's Sales Dashboard

What was the problem?

The internal IT organization of one the largest professional services firms asked us to help build a custom sales dashboard to view key client and portfolio-level financial and operational metrics. The existing sales dashboard was using aging technologies to pull and aggregate sales and revenue data from slow internal systems. Some of these systems were built for data and report processing rather than real time web use, so the existing dashboard was slow.

How we helped?

We joined their team of developers to help architect and build out the services layer with the explicit goal of sub second response times. Our team built out the caching layer to enable storage of data from downstream systems; we also built processes to periodically refresh data from the internal sources as needed, including real time data from their enterprise service bus. Furthermore we built complex business logic to do financial calculations, real time currency conversion and helped set the standard for modern single page applications within the group.

What were some of the tools used?

The application was built using Web API and .NET OData web services surfacing 10+ internal data sources. To implement the caching layer we used ElasticSearch and leveraged its ability to store large amounts of unstructured data and aggregate it at considerable speeds. We also wrote Java plugins for ElasticSearch to deal with currency conversion and other computations prior to aggregation at the caching layer. The front end was written in Angular.

What were the results?

Our team worked on the project expanding the feature set and user base for 2.5 years helping establish it as a reference architecture for modern single page applications within the organization.

Healthcare Tech Company’s Big Data And Analytics Platform

Big data challenges solved by a cloud data architecture across billions of rows of data.

Healthcare

Data Lakes and Warehouses

Healthcare Tech Company’s Big Data And Analytics Platform

What was the problem?

Our client is a healthcare education, product and technology firm whose primary focus is to activate the best possible health outcome for all patients across the globe.  The organization was generating massive amounts of data and had no way to centrally organize and report on this data across the enterprise.

How we helped?

The solution was built using Treasure Data’s cloud based Data Management platform to support the Data Lake implementation and automated ingestion of data sources.  HIVE and Presto SQL based ELT development was done to aggregate massive volumes of data to support end user reporting and dashboarding.  Tableau data sets were generated on the fly from the Data Lake and published directly to Tableau Online for end user consumption.  Additionally, Data Marts were created in Amazon RedShift to support other reporting needs via Tableau Online.

What were some of the tools used?

The solution was built using Treasure Data’s cloud based Data Management platform to support the Data Lake implementation and automated ingestion of data sources.  HIVE and Presto SQL based ELT development was done to aggregate massive volumes of data to support end user reporting and dashboarding.  Tableau data sets were generated on the fly from the Data Lake and published directly to Tableau Online for end user consumption.  Additionally, Data Marts were created in Amazon RedShift to support other reporting needs via Tableau Online.

What were the results?

Billions of rows of data were housed and aggregated to support end user on-demand analysis and executive dashboards which allowed senior management to report on the performance of their business across their various sales, marketing and content delivery channels.  Advertising data, educational content and platform performance metrics were now easily reportable from the same platform.  The platform laid the architecture to easily support reporting on future systems of record.

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