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Modernizing healthcare data management for security and efficiency

  • Healthcare & Life Sciences

Modernizing healthcare data management for security and efficiency

OneSix partnered with a healthcare data company to build a secure, scalable data platform using Snowflake, Python, and Sigma—enabling centralized data management, automated reporting, and robust governance.
Data & App Engineering
Data Analytics
Snowflake
AWS
Sigma

Overview

Scaling healthcare data with security and efficiency

A healthcare data company managing a complex network of data sources needed a scalable platform to support growing reporting needs while maintaining strict data privacy standards. With a lean team, they required a solution that balanced performance, security, and ease of maintenance. Their goals included:

  • Centralizing diverse data sources into a unified registry
  • Implementing robust role- and row-level security for end users
  • Developing a cost-effective, low-maintenance solution
  • Enabling audit capabilities, including user-level reporting activity tracking

They selected OneSix for its expertise in HIPAA-compliant environments, deep technical knowledge across Snowflake, Python, and data visualization, and its ability to provide strategic, personalized support aligned with business goals.

Our Solution

A secure, scalable, and intelligent data ecosystem

OneSix designed and implemented a modern data architecture using Snowflake, Python, and Sigma. Snowflake served as the core data infrastructure, enabling scalability, security, and governance. Cloud-based Python pipelines were used to extract, stage, and transform data efficiently.

To streamline operations and reduce data movement, Snowflake data shares were used to transition data between environments. Automated data transformations were powered by Snowflake-hosted Python scripts, tasks, and stored procedures. Row-level security and custom roles ensured sensitive data was protected at all times.

For reporting, Sigma was embedded into the client’s front-end application, delivering seamless, self-serve analytics. OneSix also supported external data-sharing needs via Snowflake and provided hands-on support for customer-specific reporting, training, and dashboard development.

Additionally, OneSix supported AI and machine learning initiatives by assisting with clinical pilot programs, leveraging EMR data, and refreshing predictive models for clinical outcomes. Snowflake’s governance tools, including built-in query history, ensured ongoing compliance and audit readiness.

Results

Driving efficiency, growth, and innovation

The implementation significantly improved operational efficiency and data governance. Snowflake-based architecture simplified data pipelines, reduced maintenance, and supported the development of new data products and services.

Key outcomes included:

  • Reduced support ticket volume through enhanced end-user training and documentation
  • Streamlined operations with lower maintenance overhead
  • New revenue opportunities through enhanced service offerings and data-sharing capabilities
  • Improved compliance and auditing via built-in Snowflake governance tools

The client reported high satisfaction with OneSix’s strategic partnership, ongoing support, and ability to deliver scalable, secure, and forward-thinking solutions tailored to their evolving business needs.

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Modernizing data architecture to unlock business insights for a financial services firm

  • Financial Services

Modernizing data architecture to unlock business insights for a financial services firm

OneSix partnered with a financial services firm to modernize its data architecture, implementing a scalable platform using Snowflake, dbt, Matillion, and Sigma to unify over 50 data sources, automate reporting, and deliver real-time insights.
Data & App Engineering
Data Analytics
Snowflake
AWS
Matillion
dbt Labs
Sigma
Fivetran

Overview

Transforming data management to drive operational excellence

A financial services firm specializing in ETF investment and technology platforms faced challenges in managing its data across multiple sources. The absence of a unified and scalable data platform hindered efficient reporting, data quality, and visibility into performance metrics, limiting the ability to meet both internal and external demands. The client sought to establish a robust data platform to support diverse use cases, streamline operations, and improve decision-making.

The goals of the project included:

  • Creating a centralized and scalable data platform for real-time reporting and insights.
  • Enabling seamless integration of data from internal and external sources.
  • Improving operational efficiency through automated reporting and analytics.

The client chose OneSix for its expertise in data architecture, cloud technologies, and demonstrated success in delivering similar solutions within the financial services industry.

Our Solution

Modern architecture and automation for seamless data management

OneSix implemented a comprehensive solution leveraging modern data architecture principles and cutting-edge technologies—including Snowflake, dbt Core, Fivetran, Matillion, and Sigma—to address the client’s data management challenges.

The project unfolded in three distinct phases:

Phase 1: Data Ingestion

  • Conducted discovery and strategy sessions to assess requirements and define the architecture.
  • Designed a secure and scalable data platform architecture using Snowflake.
  • Built a data lake to support ingestion from over 50 data sources.
  • Implemented dbt Core with Matillion for automated ETL pipelines and robust data quality tests.

Phase 2: Portal Build

  • Selected and implemented advanced ETL tools for efficient data transformation.
  • Developed a data warehouse for AUM (Assets Under Management) reporting and analytics.
  • Created an internal portal to provide teams with real-time insights into ETF performance through consolidated dashboards.

Phase 3: Additional Reporting

  • Automated 13F filings for compliance with SEC reporting rules, reducing manual effort and improving accuracy.
  • Built automated reporting for fund administration, legal registration statements, and board reports.
  • Integrated the data lake with external systems to facilitate seamless data sharing with third parties.

Results

Improved efficiency, compliance, and operational visibility

The implementation of the scalable data platform delivered measurable impact across key areas of the business:

  • Streamlined Operations: Ingested data from over 53 sources into a centralized data lake and warehouse, supporting consistent daily reporting.
  • Increased Efficiency: Automated AUM reporting and SEC filings, significantly reducing manual effort and ensuring regulatory compliance.
  • Improved Data Quality: Applied rigorous data validation using dbt Core and Matillion to maintain accuracy and consistency.
  • Real-Time Insights: Deployed internal portals and dashboards for up-to-date visibility into ETF performance.
  • Time & Cost Savings: Automated 13F filings, reducing errors and freeing up team resources.
  • Expanded Capabilities: Integrated with external systems to enable secure, scalable data sharing.

With a modern, automated data foundation in place, the client now benefits from faster decision-making, improved compliance, and a platform built to support ongoing innovation and growth.

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Reducing data processing time from 10+ hours to minutes for a pricing consultancy

  • Consulting

Reducing data processing time from 10+ hours to minutes for a pricing consultancy

OneSix helped a pricing consultancy reduce data processing time from over 10 hours to minutes by implementing a modern ELT pipeline using Azure Data Factory and Snowflake. The solution enhanced agility, scalability, and confidence in pricing insights.
Data & App Engineering
Data Analytics
Snowflake
Microsoft Azure

Overview

Unlocking faster, scalable pricing insights

A strategic pricing consultancy faced challenges in processing large-scale customer pricing data. Their existing solution relied on Python scripts and Excel, which struggled to handle the increased data volume from a new customer. Processing times ballooned to over 10 hours, making iterative analysis impractical and hindering their ability to provide timely pricing insights.

The consultancy needed a flexible, scalable, cloud-based solution that could process data rapidly, support iterative experimentation, and lay the groundwork for a pricing platform that could accommodate additional customers while maintaining data security and isolation.

Our Solution

A modern ELT pipeline to optimize data processing

OneSix designed and implemented a modern ELT (Extract, Load, Transform) data processing pipeline leveraging Azure Data Factory and Snowflake. The architecture streamlined data ingestion, transformation, and analytics, delivering rapid performance and scalability. Key elements of the solution included:

  • Automated Data Ingestion: Azure Data Factory ingested raw customer data on a scheduled basis into the client’s Snowflake environment.
  • Medallion Architecture: The pipeline followed a medallion architecture (bronze, silver, gold layers) to clean, enhance, and transform raw data into actionable pricing insights and recommendations.
  • Data Processing: Processing was conducted with a combination of Snowflake SQL and Python for flexible and powerful transformations.
  • Interactive Analytics: A Snowflake Streamlit application allows customers to view insights, experiment with pricing configurations, and analyze results in real time.
  • Seamless Data Export: Azure Data Factory exported processed data products into the customer’s SQL database for further analysis and reporting.
  • CI/CD Integration: The entire Snowflake environment was managed using CI/CD pipelines via GitHub workflows and Snowflake’s Git integration tools for declarative schema management.
Technologies Implemented
  • Snowflake
  • Python
  • Azure Data Factory
  • Streamlit

Results

Achieving fast performance, enhanced agility, and seamless scalability

The solution drastically improved data processing efficiency, reducing execution time from over 10 hours to just minutes or seconds. This rapid performance enabled:

  • Faster Iterative Analysis: Clients could quickly experiment with changes to the pricing engine and configurations, facilitating a more iterative and agile approach to pricing strategy.
  • Enhanced Confidence: The ability to rapidly analyze data and refine pricing models helped build confidence in the pricing recommendations and insights provided.
  • Scalability and Flexibility: The architecture laid the foundation for onboarding additional customers seamlessly, with reusable components and strict data isolation for security.

The consultancy praised the performance and adaptability of the new solution, highlighting how the architecture enabled rapid, iterative development and delivered consistent, high-quality pricing insights.

"OneSix’s solution transformed our data processing capabilities. What used to take hours now takes seconds, allowing us to experiment and deliver pricing insights with unprecedented speed and accuracy."

Ready to unlock the full potential of data and AI?

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Unifying data for enhanced portfolio insights and reduced risk​ in private equity

  • Financial Services

Unifying data for enhanced portfolio insights and reduced risk​ in private equity

By creating a scalable, unified data infrastructure, OneSix enabled a private equity firm to gain a comprehensive view of portfolio performance, improve decision-making, and drive long-term profitability.
Data & App Engineering
Data Analytics
Snowflake
Matillion
Fivetran

Overview

Building a modern data infrastructure for strategic agility

A private equity firm managing a diverse portfolio of investments faced challenges in leveraging data for strategic decision-making. The firm recognized the need for a modern data infrastructure to consolidate disparate datasets, enhance analytical capabilities, and gain deeper insights into overall portfolio performance.
The existing data infrastructure was fragmented, leading to delays in reporting, inefficient data processing, and a lack of agility in adapting to evolving business requirements.

Our Solution

Data unification across portfolio companies

OneSix built a modern data infrastructure, which is essential for centralizing data and gaining deeper insights into overall portfolio performance. This involved creating a unified data repository to integrate and store data from various portfolio companies, providing a unified view for analysis and reporting.
As the firm increases the portfolio, the architecture was designed to allow seamless scalability, accommodating growing datasets without compromising performance. The solution leverages Snowflake’s data sharing features to securely share relevant data between portfolio companies and the PE firm, fostering collaboration and knowledge exchange.

Results

A holistic picture of portfolio performance

The implementation of a comprehensive data infrastructure provided the private equity firm with a holistic view of portfolio performance while ensuring data security and integrity.

This empowered the firm to make more informed decisions, enhance operational efficiency, and gain deeper insights into their investments, ultimately mitigating risks and fostering long-term profitability.

Ready to unlock the full potential of data and AI?

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Building a Customer 360 data solution for Leader Bank

  • Financial Services

Building a Customer 360 data solution for Leader Bank

By implementing a unified Customer 360 data solution, OneSix enabled Leader Bank to enhance customer service, drive data-driven marketing, improve data quality, and boost operational efficiency.
Data & App Engineering
Data Analytics
Snowflake
Matillion
Fivetran
Power BI

Overview

Overcoming data silos to gain a unified view of customers

To maintain a competitive edge, community banks need to have a deep understanding of customer behavior and preferences. Leader Bank, like many financial institutions, faced a common challenge: fragmented systems and data silos. They had separate platforms for commercial lending, residential lending, and core banking operations, with little interaction between them. This siloed approach made it incredibly difficult to establish a comprehensive view of their customers.

Back-office processes were cumbersome, and customer support teams found it challenging to provide efficient service due to a lack of unified customer data. To compound matters, data quality issues, including inconsistent naming conventions and formats, added complexity to the situation.

Our Solution

Implementing a Customer 360 platform with a cloud-based infrastructure

OneSix partnered with Leader Bank to tackle these issues head-on, devising a comprehensive solution that aimed to provide a holistic view of each customer. The key components of this solution included:

  • Master Data Management (MDM) Strategy: OneSix developed a robust MDM strategy to standardize data across the organization, ensuring consistent naming conventions and formats. This laid the foundation for accurate data integration.
  • Cloud-Based Data Infrastructure: To create a unified platform for customer data, OneSix implemented a cloud-based data lake and data warehouse. This allowed for the storage and processing of vast amounts of data from different systems in a scalable and cost-effective manner.
  • Rules Engine: A rules engine was introduced to automate data validation, cleansing, and transformation. This ensured that data was accurate, up-to-date, and adhered to the defined standards.

The goal of these components was to establish a common data platform where information from various systems could seamlessly integrate. This would enable Leader Bank to tie together customer interactions, track their history, and gain valuable insights for personalized marketing and improved customer service.

Technologies Implemented
  • Snowflake served as the host to collect data into the data lake across various systems. A C360 data warehouse served the BI and Customer information needs of this bank.
  • Fivetran was used to capture data across a variety of data sources to move data into the data lake. In addition, Snowflake Data Share provided access to raw data for a Snowflake-based system.
  • Matillion was used as the rules engine to cleanse data and provide match/merge rules for the customer record and transform that into the data warehouse.
  • PowerBI was used to drive analytics and display Customer 360 information across the institution.

Results

Enhanced customer service, data-driven marketing, and operational efficiency

The implementation of the Customer 360 solution brought about significant positive changes:

  • Improved Customer Service: With a unified view of customer data, the bank’s support teams could quickly identify callers and access their interaction history. This streamlined the support process, leading to improved service and reduced call handling time.
  • Data-Driven Marketing: To create a unified platform for customer data, OneSix implemented a cloud-based data lake and data warehouse. This allowed for the storage and processing of vast amounts of data from different systems in a scalable and cost-effective manner.
  • Enhanced Data Quality: The MDM strategy and rules engine led to improved data quality. Data inconsistencies were eliminated, resulting in more reliable and accurate information for decision-making.
  • Increased Efficiency by 2X: Back-office processes were streamlined, reducing operational inefficiencies. This led to cost savings and increased productivity across the organization.
  • Increased Customer Satisfaction: With improved service and personalized experiences, customers were more satisfied, leading to stronger customer loyalty and potential for business growth.

Ready to unlock the full potential of data and AI?

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Centralizing data for real-time insights and decision-making in pharmaceuticals

  • Healthcare & Life Sciences

Centralizing data for real-time insights and decision-making in pharmaceuticals

OneSix implemented an enterprise data warehouse for a pharmaceutical client, centralizing data to enhance visibility, streamline analytics, and support real-time decision-making across business functions.
Data & App Engineering
Data Analytics
AWS
Tableau

Overview

Enhancing visibility and data-driven decision-making

Our pharmaceutical client needed a sophisticated solution that provided more visibility into every facet of their operations. The company manufactures an extensive number of specialty injectable products for service providers in this space, leaning on data analytics to guide supply chain decisions as well as other core business functions.

Company leaders came to OneSix seeking our help to move beyond their limited, spreadsheet-based approach and architect a sophisticated analytics solution that provided more visibility into every facet of their operations.

Our Solution

Designing an enterprise data warehouse for unified analytics

OneSix helped design and implement a comprehensive enterprise data warehouse to manage all of our client’s analytics needs. The data warehouse is integrated with numerous internal and external systems of record, giving organizational stakeholders a single source of historical data.

Using an agile delivery process, our team was able to quickly create and roll out holistic business intelligence dashboards that could be accessed by different business units, including finance, sales, marketing, and supply chain teams.

Technologies Implemented
  • The Data Warehouse was built leveraging SQL Server RDS on AWS.
  • Talend Cloud was used to support widespread automation to quickly and effortlessly clean data and prepare it for analysis
  • Tableau Online was implemented to support advanced data visualization and ad-hoc analytics leveraging certified data sets for data governance

Results

Delivering insights and operational visibility with a single source of truth

Since implementing this comprehensive data warehouse solution, our client has enjoyed the confidence of knowing that all organizational data is stored in a single, easy-to-reach location.

Valuable information and metrics are no longer locked away in departmental silos, and stakeholders have more visibility and greater access to insights such as real-time inventory management. An integrated view now exists across multiple physical locations, leveraging sales, finance, purchasing, and inventory data in a single portal for analytics.

Ready to unlock the full potential of data and AI?

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Accelerating analytics for rapid decision-making in retail

  • Retail & Consumer Goods

Accelerating analytics for rapid decision-making in retail

OneSix implemented an Amazon Redshift data warehouse for a movie and game retailer, dramatically improving query speeds and enabling timely, data-driven insights for strategic decision-making.
Data Analytics
AWS
Tableau

Overview

Overcoming slow query runtimes to unlock valuable insights in retail analytics

Data analytics can be a major boon for any organization. But when critical workflows and processes slow to a crawl, it’s difficult for stakeholders to extract valuable insights that guide strategic decision-making.

That was the case for one of our clients, a movie and game retailer, as its Strategy and Analytics team frequently encountered query runtimes that stretched on for hours and sometimes even days at a time. Turnaround times on new analyses were significantly delayed as a result, preventing the organization from realizing the full value of big data analytics.

Our Solution

Constructing a fast and responsive data warehouse

OneSix sat down with our client’s key stakeholders to identify their most pressing pain points as well as the underlying causes. Our expert team determined that Amazon Redshift could support the business’s data warehouse and analytics needs, transitioning away from its existing on-premise SQL Server environment. We gathered requirements for content and structural changes to those sources in their new environment before loading data into the new solution.

Our team also converted the client’s existing Tableau workbooks so they would be compatible with the Amazon Redshift Data Warehouse solution. In some cases, these workbooks were rebuilt from the ground up and tested using Tableau. This new arrangement takes advantage of Amazon Redshift’s superior processing power to aggregate queries as quickly as possible.

As a result, the rebuilt Tableau workbooks displayed performance improvements that were orders of magnitude above their SQL Server-based predecessors. Tens of billions of records are now available for Strategy and Analytics teams to quickly run queries against.

Technologies Implemented
  • SQL Server, the existing on-premises data warehouse, was leveraged as a data source for Amazon Redshift.
  • Amazon Redshift operated as a ultra-fast “data-mart” solution for this client, returning high data volume queries within seconds.
  • Tableau Server and Tableau Desktop were utilized to process terabytes of data in seconds to analyze sales and inventory KPIs for.

Results

Empowering rapid decision-making with fast data queries and insights

Thanks to OneSix’s expert assistance, our client finally has a data warehouse solution that can support its high-volume data sources and deliver true business value. No longer is our client running a query and coming back after their lunch hour to see the results.

Ready to unlock the full potential of data and AI?

Book a free consultation to learn how OneSix can help drive meaningful business outcomes.

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Unlocking global sales and customer insights with for a leading restaurant chain

  • Travel & Hospitality

Unlocking global sales and customer insights with for a leading restaurant chain

OneSix created a Power BI solution for a global restaurant chain, enabling interactive, on-demand insights into sales performance and customer sentiment across international markets.
Data Analytics
Microsoft Azure
Power BI

Overview

Achieving a view of global operations for a large restaurant chain

The larger a company grows, the more difficult it is to capture a comprehensive view of its operations. Once an organization’s footprint has reached across international borders, maintaining clear visibility into every market, department and customer segment becomes challenging.

This was precisely the problem that our client, a global restaurant chain, came to OneSix to help solve. Company leaders wanted to better understand global sales performance across their core products as well as customer sentiment around their largest brands.

Our Solution

Designing a proof of concept for scalable, interactive data insights

Given the scale of the business’s operations, a new solution couldn’t simply be swapped in for the previous data warehouse platform. OneSix worked with our client’s executive leadership to design and launch a viable proof of concept that could be piloted within select business units.

Our team created a rapid prototype using Microsoft’s Power BI platform – in particular, leveraging Power Query and Power Pivot features to build dashboards and reports. Excel-based data sources were cleansed via DAX functions in Power BI.

Technologies Implemented
  • Azure DAX and Power Query were leveraged to cleanse the data and consolidate multiple Excel data files into a single data store
  • Power BI enabled interactive dashboards and reports to executive leadership

Results

Enabling on-demand insights into global sales and customer sentiment

Our client is now able to provide end users with a more interactive and visually rich way to work with their global sales and customer sentiment data.

The ability to compare global sales performance and drill into individual markets and product performance was now available on demand. The team was able to understand the capability of the new platform and identify whether or not it could be leveraged for a much larger implementation down the road.

Ready to unlock the full potential of data and AI?

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Capitalizing on IoT potential for commercial printer operations

  • Manufacturing

Capitalizing on IoT potential for commercial printer operations

OneSix implemented a data warehouse solution for a commercial printing client, transforming IoT sensor data into real-time, actionable insights that enhanced operational visibility and reduced downtime.
Data & App Engineering
Data Analytics

Overview

Unlocking IoT data for strategic decision-making

The Internet of Things (IoT) holds tremendous potential in virtually every industry and market. The IoT introduces network-enabled devices and sensors that can collect data at a large scale and produce valuable insights. The question remains for many businesses: What do they do once they have that data?

One of our clients in the commercial printing space recently grappled with this very question. It installed “electronic eye” sensors on many of its industrial printers, but struggled to convert captured data into actionable reporting that drove strategic decision-making. OneSix was brought in to help build a data warehouse solution that could facilitate operations reporting using data gathered through IoT-enabled sensors.

Our Solution

Enhancing operational visibility through data-driven insights

Our team took a process-focused approach with this project, building new processes for intake, compression, and integration of data captured by the industrial printer sensors. In addition, we combined that data with the work activity data produced by our client’s process control system.

One of the major goals of the project was to improve visibility into printing operations at a very granular level. To that end, OneSix worked alongside the company’s process engineers to develop printer-centric and job-centric views that accurately reported on the efficiency of printing operations. We also developed a web service that provides printer performance metrics with near-real-time reporting.

Technologies Implemented
  • A Prometheus time series database facilitated data collection at each printer sensor.
  • A SQL Server data warehouse provided reliable storage for both raw and aggregated data.
  • Qlik Sense dashboards displayed aggregated data for management-level reporting.
  • Grafana was used to develop shop-floor dashboards displaying real-time streaming updates on printer operations.

Results

Improved operational insights and reduced downtime

Since implementing OneSix’s data warehouse platform, our client has gained more visibility into its printer operations, including recognizing printer downtime patterns that would have otherwise gone unnoticed.

Ready to unlock the full potential of data and AI?

Book a free consultation to learn how OneSix can help drive meaningful business outcomes.

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Uncovering insights into member engagement for a digital health company

  • Healthcare & Life Sciences

Uncovering insights into member engagement for a digital health company

OneSix implemented a scalable data warehouse solution for a digital health company, enabling efficient, accurate reporting and data-driven insights into member engagement across texting programs.
Data & App Engineering
Data Analytics
Snowflake
Matillion
Fivetran
Power BI

Overview

Streamlining insights into member behavior

A digital health company was looking to better handle its customers’ needs by providing insights into member behaviors within its texting programs.

Our client provides their customers with various metrics with regard to participation and engagement in their many texting program offerings. As requests come in for new information and/or slight variations in existing reports, our client needed a better way to meet these requests.

The existing process was very manual and prone to errors, sometimes delaying turnaround time in responding to customers’ data requests. This process impeded the client’s ability to create new reports or aggregate reports across multiple programs for each customer. The current reporting could represent a point in time but did not easily allow for trends over time.

Our Solution

Building a flexible data warehouse with automated ETL

OneSix designed and built a data warehouse that could handle the client’s current and future needs in both reporting and data analytics. We created a data model that could handle today’s reporting needs while allowing the flexibility to add on later. 

Using Fivetran, we brought their source data, SQL Server and DynamoDB, into a Snowflake database. Using Matillion, we built a fully automated ETL process with fewer steps and a faster turnaround time to provide up-to-date data. The reporting and analytics are now available in Power BI.

Technologies Implemented
  • Snowflake was utilized as the data warehouse to store engagement and messaging data.
  • Fivetran was leveraged to fully replicate data from AWS DynamoDB and SQL Server on RDS to a data warehouse.
  • Matillion was used to efficiently and quickly transform source data into an appropriate schema for reporting needs.
  • Power BI provided the internal and customer facing reports for actionable insights and trends.

Results

A single source of truth for decision-making and trend analysis

With this solution and knowledge transfer, the organization is able to leverage the analytics output from our project as a template for building future reporting. A single source of truth from the cloud data warehouse allows the business to look at the numbers with confidence for decision-making.

Key financial metrics are available to view by snapshot, trends, as well as drill-down to more granular components in a visual, easy-to-digest method. The labor reporting has already yielded insight into better management of overtime for the workforce.

Ready to unlock the full potential of data and AI?

Book a free consultation to learn how OneSix can help drive meaningful business outcomes.

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