Data

Deliver an enterprise vision for data through data architecture, data management and analytics solutions. Our data strategy is supported by practical roadmaps with realistic objectives.

The opportunity for companies to leverage an increased volume of data for impactful business intelligence and improved business performance is nearly limitless. Unfortunately, the potential for the same data to cause inefficiencies and undue costs to your organization is a more common problem since many companies lack an overarching data strategy aligned to their business objectives. Very often, business leaders don’t know what data to trust and spend more time questioning the validity of the data than working together to achieve better results.

We help clients extract reliable insights, and streamline & automate decision-making by ensuring data is appropriately identified, managed and controlled.

Data sprawl, changing business needs, and increased data compliance scrutiny have placed a heavy burden on organizations. Many can only tackle these issues in silos without having a true handle on the organization’s entire data estates. Clear responsibility and dedication to the effort seems to never take hold to make the changes needed. With data management, the organization as a whole needs to change the way it thinks about data and whose responsibility it is.

Inspired by Dev-Ops, Data Operations seek to enable analytics throughout the organization as well as the creation of data products and analytical applications. Data Ops comprises the processes and tools to distribute consistent, high quality, processed data to users.

Current BI and integration teams are not equipped to offer the speed, volume, and flexibility that is needed in current enterprises. True data self-service has never been realized and business units are creating shadow IT solutions to solve data problems. Inadequate data tools and traditional architectural approaches limit the data team’s ability to respond and deliver value to the business. A data operations focus can help address each of these issues.

Analyze and document descriptive, predictive, and prescriptive models that can generalize beyond already observed examples.

Many companies have a wealth of data but lack the tools and resources to fully utilize it. Frequently, companies want to take on analytics projects but their capabilities are isolated to solve single problems rather than be accessible to the entire organization. With advanced analytics, you have the ability to access new insights based on a new way of thinking.

Becoming a data-driven organization means embracing automated decision-making as an integral part of everyday operations.

Companies have more data than ever before but struggle in realizing automation through actionable analytics. Many executives still are not seeing the value in their analytics investments because there are no actions or measurable results tied to the findings. As companies look to incorporate artificial intelligence into their enterprise systems and processes, building trust in the capabilities and reliability of quality insights is essential to achieving results quickly.

Analytics outsourcing, or managed analytics, transforms your proprietary data into insights to solve your business problems.

The expenses associated with a top analytics program – from hosting costs to expensive talent – can be burdensome to any budget. Sometimes companies find it more cost effective to outsource key components of their analytics program by using a long-term, ongoing managed analytics relationship to reduce the cost burden and improve access to data science talent and tools.