Data and Analytics

Modern Data Strategy and Enablement

Empowering organizations with cutting-edge data strategies, and harnessing modern technologies for digital transformation and business agility

What is the Impact of Ineffective Data Management?

Data drives modern organizations. Ineffective data management results in inefficiencies, poor decisions, and missed strategic objectives. Effective data management is essential for business processes such as advanced analytics, AI/ML applications, and operational KPI tracking. Without it, companies face siloed data, resource-intensive engineering, limited data availability, and mistrust in data. Implementing a robust solution is a complex effort and often falls short.

Our team can help you to optimize a data strategy: Simplify low-value tasks, enhance governance and quality, and unlock your team's potential. Enhance innovation and optimize operations with best-in-class cloud tools. Leverage metadata-driven ingestion, re-usable data engineering patterns, and centralized data storage to ensure technology effectively supports your business.

Data Strategy that positions teams to activities across the data lifecycle, so teams focus on what's important while not compromising on quality

California Consumer Privacy Act (CCPA)

Metadata Driven Ingestion with Data Contracts

Utilizing data contracts minimizes the need for complex, resource-intensive, and reactive data governance by proactively capturing core data attributes. This ensures a clear understanding and alignment of data across the organization.

Reusable Data Engineering Patterns

Implement reusable and scalable data engineering patterns to reduce platform complexity and key-person risk through consistent development standards. Incorporate best-in-class DevOps practices for streamlined development and delivery.

Centralize Standard Data Offerings

Centralize key data assets to enable innovation and experimentation without moving centrally stored data, allowing data distribution across the organization while maintaining a single source of truth.

Metadata Driven Ingestion with Data Contracts
Utilizing data contracts minimizes the need for complex, resource-intensive, and reactive data governance by proactively capturing core data attributes. This ensures a clear understanding and alignment of data across the organization.
Reusable Data Engineering Patterns
Implement reusable and scalable data engineering patterns to reduce platform complexity and key-person risk through consistent development standards. Incorporate best-in-class DevOps practices for streamlined development and delivery.
Centralize Standard Data Offerings
Centralize key data assets to enable innovation and experimentation without moving centrally stored data, allowing data distribution across the organization while maintaining a single source of truth.

Highly-tailored data products are developed by Product Teams; these are the business teams closest to the problem. A Central Platform Team supplies generic data "ingredients" that are used by the Product Teams.

Kenway’s Modern Data Strategy & Enablement

Success Stories and Thought Leadership

WHITE PAPER
Data Governance White Paper
In today’s age, the generation of large amounts of both structured and unstructured data has expan...
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CASE STUDY
Data Governance: The Key to Successful Patient Engagement
Patient engagement lies at the confluence of two dominant trends in U.S. healthcare...
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CASE STUDY
Automated Data Governance: Why Data Contracts are Key
Implementing data governance, and keeping it relevant as your data needs change, is an exercise...
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BLOG

Defining the Modern Data Stack and Its Key Benefits

Data holds the key to solving many of today’s business challenges. However, there’s a big gap between what businesses can do with data, and what they actually are doing.

Data Management Transformation: Staying Competitive in a Dynamic Landscape

Effective data management is critical to maintaining a competitive advantage.

From Manual to Automated: A Supply Chain (Optimization) Case Study

How Kenway Consulting helped a retail client take on a large-scale digital transformation of their supply chain with a sophisticated data strategy.

Frequently Asked Questions

How does Kenway's approach to data enablement differ from traditional methods?

We believe everything starts with a business problem. We see technology as a tool for the journey, not the end goal.

What are the benefits of adopting a decentralized data product mindset?

Business teams can model and use data in ways that best serve their needs, making them more agile and effective. Central teams, meanwhile, define the approaches and standards, ensuring consistency and quality across the organization. This balance fosters innovation while maintaining coherence.

How does Kenway ensure data quality and governance in a modern data ecosystem?

By employing cutting-edge approaches like data contracts, we ensure that data governance is proactive and built in from the start. This is crucial for maintaining data integrity, enhancing collaboration, and driving informed decision making across the organization.

What technology solutions does Kenway use for data storage, transformation, and discoverability?

Our approach is technology agnostic; we collaborate with your organization to select the right tool for your needs. However, we generally see success using tools like Azure Synapse, Databricks, and similar modern technologies.