DATA ENGINEERING:
Data Warehousing

A data warehouse (including data lakes) solves the common problems of companies that have many heterogeneous sources of information spread across various data storage platforms. Analysis of data across an organization’s dimensions requires reorganizing that information in a centralized location. In this way, data warehousing provides ease of access to and quality control of data without disrupting an organization’s operations.

WE DELIVER:

Increased decision-making capability

Historical views of purposefully organized data

Consistent data amongst disparate data sources

Decoupled operational data systems from analytical data systems

Increased ROI on company data

Our credentials, partners, & models

Our team holds a unique combination of skills & industry-leading certifications across the cloud ecosystem, including Cloud Data Warehousing (AWS/GCP/Azure).

We also have developed our own standardized marketing data model and suite of automated integrations called Starliner, which features:

  • Data Warehousing for Marketing
  • Audience Intelligence
  • Geo-Targeting
  • Cookieless Attribution
  • Creative Optimization
  • 360 Analysis
  • Better Reporting

SUCCESS STORIES

Multinational Pharmaceutical Co. | Comprehensive Strategy Engagement
Top British multinational pharmaceutical company builds a center of excellence through comprehensive strategy engagement.

  • Released first production dashboards within 90 days
  • Built a center of data excellence.
  • Instilled an experimentation culture and optimization capability
Read More
High Tech | Optimization Program Across Channels
Insights from personalization program drive business growth, novel opportunities, and incredible media spend savings.

  • Drove 11% growth of registrations
  • 388 net new contacts, opportunity valued at nearly $7.7MM
  • Potential of $1MM cost savings in media spend
Read More
American Cancer Society | Optimization Current State Assessment & Vendor Evaluation
The new technology and processes created by Search Discovery helped American Cancer Society increase test volume and impact.

  • 5.4% growth in YoY donations
Read More
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OUR APPROACH

Our DW services seek to understand and meet your current need—from selecting a new data warehouse technology to enhancing current technologies.

DISCOVERY

Our process starts by discovering our customers’ needs by meeting with stakeholders and reviewing business and technical objectives. We help discover the pain points that companies have, such as:

  • Accurate and Consistent Metrics
  • Easy and fast access
  • Flexibility and Scalability

Discovery will answer questions such as:

  • What is the strategic content and goals for using the data?
  • What questions should the data answer?
  • Who is this for?

TOOL SELECTION

We support a recommendation and selection criteria for a new data warehouse and/or data integration technologies. We help select and recommend tools for:

  • Integration and cleansing strategy (ETL, ELT), wherein we recommend an approach for getting the data from source to tool
  • Data flow diagram from source to tool documentation

TOOL MIGRATION

We support migrating from legacy on-premise warehouse technologies to cloud-based solutions. We determine the connection strategy for all sources within scope.

TOOL IMPLEMENTATION

We develop and implement greenfield data warehouse and integration solutions and determine the connection strategy for all sources within scope, including:

  • Schema design: Harmonization of data into the data model
  • Data Preparation: How will we harmonize all the data sources into a common model?
  • Data Modeling: What modeling techniques do we need to apply to the raw data before being consumed by analysts, BI platforms, or Data Science tools?
  • Roadmap Development

TOOL ENHANCEMENT

We optimize data warehouse performance, integration techniques, etc., by creating a current state assessment (wherein we assess the current tool and document what exists today) and a future state assessment. We perform/deliver:

  • Performance testing
  • Recommend best practices
  • System data migrations

ACTIVATION

In this phase, we perform the following:

  • Integration, Aggregation, and Feature Engineering: we automate data integration, cleansing components and aggregations for BI consumption (or features) into data science models.
  • Data Management and Governance Program development: We detail the validation process and how will users access the data
  • Project Management: We provide project execution leadership throughout the project lifecycle

LATEST INSIGHTS:

What is Datorama

Marketing Reporting and Automation with Datorama

In comparison to other dashboarding and marketing data visualization tools, Datorama combines real-time data from multiple sources to give you an accurate picture of how you’re performing across channels.

Data Mamagement Best Practice Hero

Four Data Management Best Practices

We review four data management best practices to help you make better data-driven decisions. See how our team of experts can help your business.

Ready to centralize and organize your marketing data to drive business impact? Fill out this form to chat with our experts today.

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