BROAD AND DEEP EXPERTISE

Best Practices = Optimal Results

It takes many people and many years to develop best practices. Optimal results are driven by best practices to help companies increase efficiency, innovate faster, and use technology more effectively.

With customer expectations and technology rapidly changing, most mid-market companies don’t have the luxury to develop best practices and keep them up.

Fortunately, we’ve done that so you don’t have to. We use our best practices every day to mid-market companies become data-driven organizations.

best practices

Industries

It’s important to work with someone who understands your business. We’ve worked in many major industries and our expertise is broad and deep. Below is just a sampling of the industries and KPIs we’ve developed for them.

Healthcare & Life Sciences

Manufacturing & Logistics

Financial Services & Insurance

Higher-Ed

Capabilities

Data and analytics are the key to building a data-driven organization. While we feel this is an important starting point, we can also help you put a data governance and master data management structure in place that will create a strong foundation for moving forward. And, for truly valuable insights, data science will take your decision making to the next level.

Analytics is the heart of a data-driven organization. We can help you provide self-service analytics, embed analytics into business processes, and integrate analytics with data science, all while lowering the total cost of ownership.

We leverage the best practices of each of the major analytical tool sets to make sure you use the right technology to solve the right business use cases.

Data Governance is required for any MDM, Metrics or Data Management program. Data Governance is the alignment of people, processes and technology to support ownership, definitions, requirements and value.

Structuring the Governance, embedding it into your culture, and driving compliance will be important for success and value to the organization. With our frameworks and accelerators, we can help customize them to your organization.

Your data management strategy sets the technology and architecture direction, while helping to evolve to the cloud, evaluates Platform/Software as a Service to align Modern technology with specific use cases, so you only pay for what you use.

Our methodology and lean architecture approaches, accelerate value creation and reduce complexity and heavy data movement requirements.

After clearly stating a business problem, we work with you to develop a data science strategy that defines the approach to solving it, using supervised learning and unsupervised learning models with the data, architecture and technology to support it.

Every decision within your organization should have a model to help with insights, predictions and eventually automation of the decision process. This requires the right level of governance to ensure the models are evolving with the business.

Whether Customer or Product or any other Master Data, integration and harmonization of this data is critical for the organization to treat this data holistically and not based on the constraints of any one system.

Business use cases will help determine the approach, requirements, technology, and governance required to drive value from your MDM roadmap. With years of MDM experience, we can help guide and drive you through all of these decisions.

Technologies

We have made the explicit decision to be technology agnostic and are not supported by any vendor which ensures you get the best solution for your needs. While this list is a strong representation of the tools and technologies we use, we are always identifying and vetting new products and following market trends to ensure our clients are building their future with solutions that will be part of today and tomorrow’s modern data architectures.

Snowflake
Amazon Web Services
Microsoft Azure
Tableau
Amazon SageMaker
Azure Machine Learning
Dataiku
Alation
Looker
Microsoft PowerBI

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