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Datalogz: Revolutionizing Data Management with IoT
Technology Category
- Platform as a Service (PaaS) - Application Development Platforms
- Platform as a Service (PaaS) - Data Management Platforms
Applicable Industries
- Cement
- Equipment & Machinery
Use Cases
- Building Automation & Control
- Inventory Management
Services
- Data Science Services
The Challenge
The founder of Datalogz, Logan Havern, was frustrated with the outdated and complicated modes of logging and collecting data. Traditional data management systems were not only expensive, costing thousands of dollars, but also time-consuming, taking months to implement. Moreover, these systems often resulted in data disorganization and required complicated IT procedures. The data documentation was usually confusing, commonly located in a spreadsheet or a word document. This led to a lack of a centralized repository for teams to organize their data dictionaries, answer essential questions, provide up-to-date data notifications, and publish recent work or analysis.
About The Customer
Datalogz is primarily targeted at data science and analytics teams who are in need of a modern environment to better document data and associated work. The app is also suitable for any individual or organization that deals with large amounts of data and requires a simple, efficient, and cost-effective data management system. The founder, Logan Havern, is an industrial engineer based in NYC and a serial entrepreneur. He discovered no-code tools like Bubble, which allowed him to build Datalogz without the need for technical experts, making it financially viable.
The Solution
Datalogz, a data collaboration tool, was developed to eliminate data disorganization without the need for complicated IT procedures. The app allows users to upload their data tables and create a centralized repository for their team. This repository can be used to organize data dictionaries, answer essential questions, provide up-to-date data notifications, and publish recent work or analysis. Datalogz provides a one-stop-shop for understanding data quickly and offers meta-data comprehension so users can quickly produce value from data. The app was built on Bubble, a no-code tool, which allowed for a simple and easy-to-use interface. The use of Bubble also enabled quick iterations of the product in real-time as users reported opportunities for enhancement.
Operational Impact
Quantitative Benefit
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