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A presentation by W H Inmon

ANALYZING REAL ESTATE TRANSACTIONS. A presentation by W H Inmon. There’s a lot going on in real estate today. And there’s a pot of gold to be made by understanding the marketplace. The secret to understanding the market place is understanding transactions. Sales Financial transactions

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A presentation by W H Inmon

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  1. ANALYZING REAL ESTATE TRANSACTIONS A presentation by W H Inmon

  2. There’s a lot going on in real estate today

  3. And there’s a pot of gold to be made by understanding the marketplace

  4. The secret to understanding the market place is understanding transactions Sales Financial transactions Loans, loan rates Consumers

  5. Recording by county of a deed of trust

  6. County recording of a loan

  7. Inline contextualization Taxonomy/ontology resolution Custom variable formatting The three primary types of transformations done In order to turn raw text into a standard data base

  8. textual ETL unstructured data taxonomy Standard data base real estate transactions Oracle DB2 Hadoop SQL Server Teradata Netezza visualization 50,000,000,000 records Tableau SAS Qlikview Cognos Excel Many others The general architecture

  9. The output is a data base in a normalized structure

  10. Record id Context descriptor Value of interest

  11. recorder residence lien filed city state

  12. recorder residence lien filed city state

  13. Query - Find all sales in Arizona for month of May Find all commercial sales less than $500,000 for 1st quarter Find all loans granted in June where rate is less than 3.75% You are only limited by your imagination

  14. textual ETL unstructured data taxonomy customer response visualization statistical analysis Tableau Once you have your data in a data base and in a relational structure, you can analyze it any way you want

  15. textual ETL unstructured data taxonomy With a data base in a normalized structure, you can ask all sorts of questions - Real estate transactions How many sales were made in Arizona this month? How many sales were between $250,000 and $1,000,000? How many commercial sales were there? What is the loan to equity ratio? And many, many more questions

  16. textual ETL unstructured data unstructured data taxonomy Two approaches to doing the same thing automated manual manually

  17. Textual ETL Cheap Fast Accurate automated Expensive Slow Error prone manual

  18. textual ETL unstructured data taxonomy visualization statistical analysis Tableau Now you can go from textual data to meaningful analysis

  19. textual ETL unstructured data taxonomy visualization Now you are set for the “AHA” moment!!

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