Client needed to move from on-premise MAPR solution into the cloud in order to take advantage of cost savings and match timelines with a larger initiative. The Google Cloud Platform (GCP) was chosen and using our GCP DataProc (EMR/Spark) conversion and testing process to ensure accuracy, all workloads were moved successfully. HDFS was replaced with GCP Storage and additional analytics and machine learning initiatives also allowed for project visibility and project goals to be met.

A mid-size healthcare provider required its management to determine the profitability of its affiliates (i.e.: customers) across several business lines. Although the ERP system in-use provided standard financial reporting information such as P&L outputs, the ability to pivot in the system to provide more analytical reporting, such as the profitability of a customer across business units, by quarter, location, etc. and then to drill down into the most sold products or utilized services was not available.

AICG leveraged its expertise in healthcare as well as technical knowledge to produce an end-to-end solution which allowed finance users in the organization to quickly retrieve the data through MS Excel on an intra-day frequency. The ROI on this solution was measured by the actionable intelligence to collect unrecognized revenue and resource time reclaimed from previously having multiple resources attempt to manually produce portions of the solution that were consuming 20% of their time each week.

Looking across clinics and other field locations data from inventory, product, and services could not be consistently reported in a timely matter. Disparate product codes and legacy systems required hours of internal wrangling which led to inconsistencies. Additionally, exploration of exceptions using business logic was maintained with one resource and often not repeatable in a timely manner. Executive reporting was often late when requested adding frustration to an organization that was in the midst of restructuring. 

AICG provided the business consultation, to provide a temporary and strategic long-term solution involving: data ingestion to include business logic rules, augmenting staff for the silo’d resource, adding machine learning to identify and predict outliers/inconsistencies in form submissions, and a data model that allowed for the consolidation of legacy systems reporting data. A new analytics system implementation then provided distribution of production reporting to the correct line of business requesters.

Multiple store locations needed to be consolidated into a single, flexible source-of-truth for financial and operational sales reporting. A larger marketing initiative under way required sales POS data at a sales flash level in order to align management decision making across regions, roll-up to corporate, and reporting to the board of directors. Our pre-built solution enabled a data integration pipeline, and provided analytics at different levels for regional managers, executives, and board members.

One of our latest projects centered around a high-tech company using commercial real-estate HVAC monitors and other IoT devices, where the requirement was to merge high velocity date through AWS streaming (firehose) and into Snowflake and combine other lower velocity customer metadata into a single source repository for analysis by the building managers and other personnel so that system anomalies and inspections could be acted on in near real-time. The project included Snowflake, DBT, Advanced SQL, Looker, and DataLakeHouse.io technologies to make this project initiative a success.