Real Estate Data Setup and Map Creation in Maptive IQ скачать в хорошем качестве

Real Estate Data Setup and Map Creation in Maptive IQ

In this Maptive IQ tutorial, we walk through how to structure real estate data and turn it into a functional, interactive map. This video provides practical ideas for what fields to include in your dataset and demonstrates how that information can be used once it’s loaded into the platform. The example shown leans toward commercial real estate, but the structure applies equally to residential, mixed-use, industrial, retail, or land portfolios. You’ll see how to organize a dataset that includes acquisition date, full address (properly broken into columns), year built, square footage, property type, occupancy status, occupancy rate, weeks on market, and property status. The tutorial also covers building amenities and how to structure attribute-style columns using semicolons. For example, amenities such as public bathroom, private bathroom, elevator access, or parking can be separated by semicolons within a single column. Maptive IQ recognizes this format and allows you to filter those attributes individually using the filter tool. This makes it possible to store multiple characteristics in one column while still maintaining control and segmentation inside the map. You’ll learn the basic formatting requirements for clean imports: • Column headers must start at row one, column A • No blank rows or blank columns • Data should begin directly below the headers The video explains that your dataset can be extensive, whether it includes thousands of properties or large file sizes, as long as it stays within platform limits. Once your data is saved, the tutorial walks through creating a new map by uploading a file, copying and pasting data, or connecting through Google Sheets. After importing, you’ll see how your data appears in the Data tab exactly as it was structured in your spreadsheet. From there, you can begin using grouping tools, filters, and other map features to segment properties by type, status, occupancy, amenities, or any other field you included. This tutorial is intended for real estate professionals, property managers, brokers, investors, and analysts who want to organize portfolio data visually and make it easier to filter, review, and present. Timestamps 00:05 Introduction to real estate data mapping 00:13 Data ideas and inspiration 00:21 Commercial-focused example (applicable to all property types) 00:34 Key data fields to include 00:47 Extended property data examples 00:55 Using semicolon-separated attributes for amenities 01:11 Filtering amenities with the attribute filter tool 01:24 Adding useful custom data columns 01:30 Spreadsheet formatting requirements 01:57 Dataset size and limits 02:06 Creating a new map 02:17 Uploading, pasting, or using Google Sheets 02:36 Viewing your data in the Data tab 02:53 Filtering and grouping by property data 02:58 Closing