Case Studies

Delivering success to clients from around the world and from a variety of industry verticals, companies of all sizes, from startups to Fortune 500 and Fortune 100 companies.

iRobot Case Study

To automate and improve these processes, our DevOps team has built over twenty unique CI/CD pipelines with each being deployed across multiple environments (AWS accounts).
Dianomi’s platform serves more than 8 billion content ads per month reaching a global audience of over 400 million devices.
Capture & process streaming data from more than twenty (20) million devices globally for advanced analytics.
Endeavor is one of the largest private operators in the United States.
RSI’s machine learning platform can now support any workload regardless of volume, velocity, and variety of data. As a result, business users have more trust in their data.
AWS based infrastructure was key to take full advantage of that allowed their solution to go to market quickly and scale securely and cost effectively.
TCO reduced by 54 percent. AWS enables Dickey’s to scale at a fraction of its on-premises cost.
FrontBurner required a modern architecture that could consolidate its existing disparate warehouses into a single enterprise data hub.
iOLAP and Maui Jim partnered together again to accomplish each initiative
Robust solution, with faster data delivery times and cleaner data, driving a positive ROI.
nOps Azure Integration
Less time spent on support customer calls due to faster search for the correct record or customer identification and their assets.
Performance tuning and regular database maintenance led to considerable reduction in average query times; from 15-25 seconds down to 2-4 seconds.
Legacy code translation into technical design documents in support of enterprise data warehouse partner.
Extract data from all global locations based on local, specific labor laws, allowing for GWM partner to track time and perform statistical reporting.
Enhanced the stream capacity to handle the SLA of several terabytes per day. Work with data suppliers on new streams for additional data topics.
ETL project delivered a single source of truth and also allowed for a multitude of systems to be retired.
iOLAP partnered with the client to develop a Data Lake in Azure, Enterprise Data Warehouse (EDW) in Snowflake and Reporting/Dashboarding in Power BI.
Maui Jim Creates Enterprise Data Hub with iOLAP and AWS
Custom solution for extracting, shaping, validating, and processing input data for more than 60 data sources in a variety of formats and velocity.
Designed and implemented code to perform member matching using numerous different name-matching rules to identify the customer.
Redesigning the process, migrating the data and bringing automation to work.
Integration of important functions with comprehensive loan data provides unlimited possibilities and reduces risk, improves efficiency and drives financial performance.
Protected customer data is one of the top security challenges of modern times, especially financial data.
Focusing on harvesting impression information across conformed dimensions. What took days is now created in minutes.
Installations optimized with Netezza best practices to deliver operational efficiency to various business units.
New data management platform that increased analytical capability and performance, to further enable new product features including one-to-one marketing,
Redshift data warehouse optimized to support a broad array of analytic functions to drive intelligent business decisions.
A set of OBIEE reporting modules were implemented and customized to meet customer reporting requirements.
Online customer behaviour data made valuable and resulting in more clicks and leads.
Building a customer-centric warehouse on Netezza allowed accurate customer data, faster report creation, customer segmentation, and selling efficiencies.
Leveraging the new Netezza and Hadoop platform enables to identify potential fraud transactions across all locations in near real-time basis through automation.
Striper server and best practices cut nightly load times from 4 hours to 45 minutes and allowed for new options and future expansion in ETL and Reporting.
Better and faster decisions in web analytics, which drove an improved user experience. 0.2% gross demand increase delivered annualized benefits equal to a 10x ROI.
Running critical models to predict equipment failures, improve well operations resulting in significant cost saving.
SAS is able to easily gather and process the data, and produce the required analytical reports in a timely manner.
Data processing and reporting are completely automated. What used to take days to produce is now accomplished in a matter of minutes.
Data strategy that addresses the needs of end users, determining the correct balance between centralized and decentralized data.
One unified and trustful data source for the whole organization that enables better management and faster response rates.
Running reports and accessing all historical data to make past years comparisons with just one version of truth throughout the organization.
Dashboards creation to report productivity and workloads to streamline process flow, which reduced turnaround times by an average of 25%.
Solution creation that captures and analyzes EKG images using custom computer vision code. These EKG results are compared with patient data to determine a personalized risk assessment.
Data Warehouse model created that provides performance and longevity while allowing for festering of the growing company.
Building with data full profiles of customers including purchasing habits and both geographic and time-based fashion trend.
AWS based solution enables HAS to unlock the true value of data and anticipate traveler needs while forecasting future revenue opportunities and challenges.
Implementation of PUB/SUB architecture, which reduced the load on Teradata, and resulted in savings of millions of dollars.
Analyzing data at an atomic level in one place which is easily accessible and made available to them in a timely manner.
Big savings achieved with the implementation of the ability to see the results of financial record changes shortly after they are made.
Executing in excess of 2 million queries per day with an average response time of < 1 second.

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