Meet Cherre
Commercial Real Estate decision-makers face the daunting task of obtaining and analyzing precise property and market information to make smarter, faster decisions. Cherre has emerged as a leading force in Real Estate data and insights, creating a unique single source of truth for its customers by integrating their internal, public and paid data sources. This empowers customers to evaluate opportunities and trends quickly and accurately, translating into significant cost savings in terms of data integration, physical entity resolution, and analytical insights.
The Challenge
Cherre faced critical challenges in accurately resolving relationships between physical entities like buildings and associating vast amounts of information with these entities. The physical entity resolution problem involved semantics, legal definitions, property registration practices, and geographic scale issues. Cherre needed to rapidly and accurately resolve building identity to link disparate datasets from multiple sources while staying within service level agreements.
The Solution
Cherre uses Google Maps Geocoding API and Places API to analyze and convert millions of street addresses into geocodes. DoiT assisted Cherre in providing Google with detailed information to increase the rate of address resolution procedures. This enables massive geocoding in short timeframes. Cherre then utilizes BigQuery Geospatial for spatial analysis to rapidly link and integrate datasets. DoiT's consultancy helps Cherre plan, manage and optimize BigQuery activities through the DoiT Console and BigQuery Lens functionality.
Results
- Enabled massive amounts of geocoding in short timeframes while meeting SLA requirements
- Achieved significant cost savings in data integration, physical entity resolution, and analytical insights
- Provided customers with accurate and timely real estate data insights while saving resources in manual data processing
By leveraging a range of Google Cloud and Maps products and the expertise of DoiT, we have been able to solve critical challenges, such as entity mapping and address reconciliation, while saving considerable resources in data integration and analytics costs.
Kyle Lussier, Data Engineer
BigQuery Optimization
Once all the datasets have been geocoded, Cherre utilizes the powerful spatial analysis functionality of BigQuery Geospatial to rapidly link and integrate the datasets. DoiT's consultancy and technology have been instrumental in helping Cherre plan, manage and optimize its BigQuery activities. Via the DoiT Console, Cherre can observe and control BigQuery costs with the multi-report breakdown capabilities, utilize the BigQuery Lens functionality, and share optimization insights with the rest of the organization.
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What they say
What I really like about DoiT's approach is that you're very hands-on and proactive. Satyam would ping me a few times a sprint, letting me know about the most current features, checking in on how things are going. When we are going through a peak time, that proactiveness makes a real difference. Satyam always comes through whenever we need support and helps us leverage the right experts to get us where we need to be.
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I love clicking through SELECT to understand how our environment and workloads are evolving. I probably check it every day. It's coffee and SELECT for me every morning.
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You guys have the best UI experience that I've had of any software. It's like you just read my mind where, like, oh, I wish I could click there. Oh, I can
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DoiT was a true partner, not a vendor. They helped us understand the problem, refine the vision, and build something production-ready far faster than we could have on our own. Their expertise, responsiveness, and commitment made all the difference.
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DoiT's Customer Success and Forward Deployed Engineering teams work very closely with us. The regular sessions with our CSM keep us focused on the right priorities, and the FDEs provide the deep technical guidance we need to validate decisions and optimize our environment. That combination has been genuinely valuable for us.
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