Concept (Further reading)
Deep dive into the concept of Codatum.
Last updated
Deep dive into the concept of Codatum.
Last updated
Modern enterprises hold vast amounts of data in a different formats. This data needs to be reshaped, transferred, downsized, and accessed by different teams through different interfaces.
This process makes it challenging to access all the data, return to the original data, and coordinate tasks across teams, leading to stagnation in the analysis cycle.
To solve this, a unified user interface capable of handling everything from large-scale to small-scale data, and from reshaping to analyzing data, is essential.
SQL has long been a code-based interface for data and should have functioned as this unified interface. However, SQL faces several challenges, such as difficulty in previewing, saving, sharing, and dividing queries.
By seamlessly integrating SQL with a modern user interface and modern concept, we believe that Codatum can overcome the fragmentation of data, processes, and teams, significantly accelerating the analysis cycle for enterprises.
Many BI tools are designed for ease of use, targeting business users for simple tasks. However, data analysis is inherently complex. Existing tools often fail to provide the depth needed for meaningful insights, and are too restrictive for data scientists and engineers.
With Codatum:
It goes beyond simple tasks, requiring some technical knowledge like coding, and supports deeper analysis.
It enables technically skilled team members to fully engage in data analysis.
SQL is central to data analysis but challenging to manage and share, especially when dealing with complex queries.
With Codatum:
A keyboard-centric UI lets you modularize SQL and develop while viewing results, making complex data easier to handle.
It enhances collaboration, allows for folder-based management, and enables the creation of beautiful dashboards for sharing.
Jupyter Notebook has long been a staple in data analytics, but its traditional workflow, involving data transfers from Data Lakes to Data Marts and then into Python sessions, is becoming outdated for real-time analysis. These tools, focused less on SQL, often blur the boundaries necessary for efficient data handling.
With Codatum:
Access fresh, accurate source-of-truth data directly from Data Lakes or Data Warehouses, facilitating more precise data analysis.
Collecting and organizing quality data is crucial for complex analyses, which should be iterative rather than linear. Codatum enables seamless SQL integration for both data modeling and analysis on the same platform, reducing unnecessary delays during analysis cycle.
With Codatum:
Preprocessing, modeling, and SQL subquery management are integrated on a single platform, speeding up the data preparation and analysis cycle.
Security and privacy are critical in data analysis, requiring tight access control to minimize risks while maximizing data utility. Without detailed permissions, analytical flexibility is severely limited, diminishing the value of data assets.
With Codatum:
Granular permission controls enhance security and allow for expanded data access, ensuring that data reaches only those who need it without compromising privacy.
Codatum is designed to leverage the power of data to strengthen teams. By eliminating data fragmentation and promoting collaboration across teams, Codatum maximizes your team’s potential with a data-driven approach. Enjoy the benefits of using Codatum!
Read more about our choice of block editor over cell-based editor here.
