Is your data
answering
your
questions?

Data strategies that empower teams with real-time access to accurate KPIs and intuitive visualizations from multiple systems across your entire organization.

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Better

Better Data,
Better Decisions

A foundational component of digital transformation is a modern data architecture that enables better data-driven decisions across the organization.

Most mid-market businesses are saddled with a set of highly manual processes that string together data sets from multiple systems to answer very important questions via KPIs, often with a high degree of error and inaccuracy.

Modern data architecture democratizes and expedites your data so that KPIs, data visualizations and other business intelligence flow freely through your enterprise.

REEA Global Analytics Maturity Model

Stage 1

Data Evangelism

Before beginning any data and analytics program, the REEA Global Team works with you secure buy-in from stakeholders within your organization. Driving adoption and initial excitement about how the power of data can help everyone work more efficiently is core to our process.

Stage 2

Enterprise Data Warehouse (“EDW”)

The need for most organizations to consolidate data across multiple sources is generally what drives data analytics programs. An Enterprise Data Warehouse allows for metrics from multiple sources, business logic and data transformations to live in one centralized location.

Stage 3

Reporting & Operational Support

Reporting and operational support involves reporting out on basic KPIs and metrics using the EDW. This is generally the first evolution of reports, where metrics may be reported in tabular or graphical formats and consumed by operational staff and executive management.

Stage 4

Advancing Analytics

The first stage in helping organizations evolve from basic reporting to developing an infrastructure that allows for them to better understand their business and ultimately answer more complex business questions.

Stage 5

Predictive Modeling

Leveraging the infrastructure and key learnings from Stage 4, Predictive Models help organizations look toward the future and develop better forecasts based on historical data.

Stage 6

AI & Machine Learning (“ML”)

AI & ML are areas in which machines and algorithms develop an understanding of data to execute advanced predictive and prescriptive models, ultimately developing intelligence. AI & ML are heavily dependent on model development and maturity of data in order to advance.

Data Services

1

Data Infrastructure
Review Program

A 3rd party holistic assessment of an institution’s data infrastructure and lifecycle.

2

Data Infrastructure &
Operations Consulting

Operationalizing the DIR Program recommendations and implementation.

3

Data Quality
Assessment Program

A Holistic, deep dive of an institution’s data quality program.

4

Data Quality Action
Plan Consulting

Operationalizing the DIR Program recommendations and implementation.

Put Data Technology to Work for You

We help stakeholders get answers to their questions by implementing overarching data strategies that enable descriptive, predictive and prescriptive analytics. With REEA Global as your data technology partner, you’ll know that your data is safe, scalable, accurate and visualized in a way that allows business intelligence to flow freely throughout your organization.

  • 1. Data Infrastructure & Quality Review. A holistic assessment of your company’s data infrastructure and data quality program with a focus on data warehousing, business logic and the management of data pipelines.
  • 2. Planning. Identifying the data methodology, tools, visualizations and reports that are best suited for your business.
  • 3. Execution. End-to-end implementation of your company’s unique data program. REEA Global’s implementation team includes data warehousing engineers, analysts, and visualization experts.
  • 4. Training & Onboarding. We provide hands-on training for everyone on your team to help them find the data, interpret it, identify themes and convert them into actions.
  • 5. Monitoring. Ongoing monitoring of data infrastructure to identify flags that impact data accuracy.

DIR

Data Infrastructure
Review

Assessment of your current data infrastructure and pain points related to getting the most out of your data. We review all existing data operations and provide a comprehensive audit with recommendations of:

  • Data infrastructure maturity
  • Data operations maturity, including operational best practices
  • Data quality practices and methods in place
  • Data preparation and transformation practices
  • Enterprise data warehouse/data lake data models
  • Technical infrastructure, including visualization of data models, technologies and workflows

DQR

Data Quality
Review

Detailed audit focused on helping you understand how data quality is measured, managed and optimized; as well as how these factors impact decision making and daily operations. The in-depth analysis of the data quality program will include:

  • Detailed volumetric analysis of each stage of the data infrastructure (source systems, landing, preparation, reporting)
  • Review of data models in depth
  • Data quality practices and methods in place
  • Detailed quantitative and qualitative analysis of KPIs from reports

DIOE

Data Infrastructure &
Operations Execution

Implement the foundation which will enable seamless access to KPIs and data visualizations using data sets across multiple platforms and departments. With experts in every step of the implementation process, we’re able to provide you with a comprehensive solution.

  • Implement a high-level data strategy, including an approach to analytics and technical infrastructure
  • Champion and drive adoption of the data strategy with leadership
  • In-depth review of roles and responsibilities for existing employees, consultants and potential new hires
  • Drive implementation with hands-on approach, dependent on staff plan

DQM

Data Quality
Monitoring

Develop and maintain a data quality program that ensures the accuracy of organizational intelligence and ensures that your team mitigates risk moving forward.

  • Detailed volumetric analysis of each stage of the data infrastructure (source systems, landing, preparation, reporting)
  • Review of data models in depth
  • Data quality practices and methods in place
  • Detailed quantitative and qualitative analysis of KPIs from reports

Experience

We speak your language

We pride ourselves in delivering custom data strategies that everyone understands. In speaking a common language and providing end-to-end solutions, our data analytics services drive real ROI to companies that understand the value of data-driven decision making, but don’t quite know where to start. Leave the tech talk to us, and focus on what you’re really good at -- growing revenue, empowering your team to make smarter decisions and building a better brand.