Data317

How would you like neighborhood-level socio-economic, demographic, and housing data for the whole country to prove your market, find customers, and identify locations... for free? That’s not a cheesy tagline; it's a reality. Many consultants charge a small fortune—recently saw one in particular north of $26K—for data often collected by the Federal government and freely available. One such resource is the American Community Survey (ACS). The ACS data, annually updated by the US Census Bureau, includes over 30,000 variables collected at various geographical levels (country, state, county, zip, census tract). It is easy to work with in Excel or Tableau and contains valuable information like: - Income ? - Housing Costs - Industries / Professions Employment - Education levels - Health Insurance Coverage - SNAP, SSI benefits - Housing situations?(like multigenerational, commuting patterns) - Tons more (working from home example, on a log scale below!) And the best part? It’s completely free. I’ve used it to build market segmentation models, determine optimal locations for hospitals, and help food pantries better serve their neighborhoods. It’s a solid foundation for impactful AI work and can complement your own collected data in a powerful way. Check it out (and save some cash)! Link: https://lnkd.in/esv5derV

Why can?#AI?fall short of expectations? More often than not, it's because AI was the starting point for a solution. Starting with AI is so tempting! We've worked on hundreds of AI projects, and the results can feel like magic! However, starting with AI can lead to superficial implementations that solve symptoms rather than the root cause of a problem. How can you avoid the trap of?#BoltOnAI? In our latest blog post, we share our approach to data problems that address the root cause of a problem and ensure effective, lasting solutions. Check it out!