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Data Quality Matters

Better data generates better results.
Following data best practices can help you get there.

Data Challenges

I want you to win with data but that does NOT happen by accident.

Winning with data is a lot like winning in sports. No one wins by just showing up to play on game day and hoping for the best. Teams that win consistently are Highly Intentional about their preparation and do off season workouts, conditioning, practice and film study to give themselves the best chance of winning on game day.

These are the most common challenges I see in organizations regarding data. Do any of them sound like your organization?

Data Quality

Data quality is a core feature of data management along with governance and data standards. No matter how good your data product might be, if your quality is off, your results will be too. Data Quality considers six dimensions: Completeness, Consistency, Accuracy, Timeliness, Validity and Uniqueness.

Disconnected Data

Most organizations have data spread across multiple apps, spreadsheets and files perhaps across departmental boundaries. And none of it works together. This is called a data silo in the data business. This is fixed using a variety of integration methods to provide a more unified view of the big picture.

One Size Fits None

The generic off the shelf software solution. Its like putting a square peg into a round hole, it just doesn't work very well. Then all you get are canned reports when you really needed something custom.

Manual Processing

Manual data processing is time consuming and error prone. The solution is to automate data processing so that it is consistent and reliable using preset checks and processing rules that run on a schedule.

Hi, I'm Joe

I've always been drawn to data because it tells the story of how we got here and where we want to go.

Formally education in Urban Planning, I think strategically ever since. I have also done work involving Geographic Information Systems, Software Engineering and Data Engineering.

Sum total, I have worked with data for 20 years and written code for 12 years completing more than 80 projects along the way in a variety of roles and capacities for organizations ranging from the small family business to large enterprises with thousands of team members.

I am a Certified Data Management Professional which gives me a comprehensive understanding of data best practices regardless of technology.

Ultimately, I view my most effective role as that of a Data Architect as it mixes both the strategic planning found in Urban Planning and the technical used in Software and Data Engineering.

Focus Area

My primary area of interest is in Data Quality and working with Databases at a high level.

I also maintain an interest in Urban Analytics which is the blending of Urban Planning and Data Analytics using technologies such as Geographic Information Systems as well as adjacent industries including Economic Development, Real Estate and others.

Below are selected types of projects I have done in these areas.

Data Engineering

Automated data integration and processing from a myriad of sources featuring Data Pipelines, ETL, Cleaning and Enrichment.

Data Apps

Facilities Management, Asset Management, Document Management with Text Analytics and Capital Expenditures.

Web Development

Websites to market Urban Planning, Economic Development, Entertainment Venues and Outdoor Recreation with GIS integration and E-Commerce.

Managed Analytics

I help organizations with data so its done right.

I ensure they have the right data at the right time at the right destination in the right format.

This involves three distinct functional areas that are all related. These are Data Management which enables good Data Engineering to build robust backend systems which then enables the development of good Data Products.

Brick building

Data Management

Good data management enables good data engineering.

  • Governance
  • Quality
  • Metadata
  • Master Data
Code on laptop

Data Engineering

Data engineering builds robust data systems to power data products.

  • Data Modeling & Database Design
  • Data Pipelines & ETL
  • Data Warehouse
  • Data Processing & Analysis
Dashboard on a tablet

Data Products

Data Products are easy to use and consumed by the end user.

  • GIS & Geospatial Analytics
  • Business Intelligence
  • Data Apps
  • Web Development