AUDIT123

web service/app powered by WEBMIND28

The primary task of the Audit 123 project was to develop a comprehensive data visualization system capable of processing various types of financial data, including loan repayments, post-dated checks, and other critical financial transactions. This system needed to support multiple file formats, provide detailed analytical data through graphical representations, and be user-friendly for the staff.

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The CLIENT:

Ziv Schiffer & Co., one of the largest accounting firms in Israel, provides a wide range of services, including a personalized approach by senior accountants, effective tax planning, pension consultations, credit procurement, and advanced online services with technological innovations to streamline processes.

The Challenge:

To address this task, Webmind28 was hired to develop and implement an advanced data analysis platform. This included:

  1. Developing a user-friendly interface:
    • Ensuring that the platform was intuitive and easy to navigate, allowing users to access and analyze data without technical knowledge.
  2. Implementing support for various formats:
    • Enabling the system to analyze data from unified files, Excel files, and control files seamlessly.
  3. Creating detailed graphical representations:
    • Developing tools for data visualization, such as tables, charts, and graphs, to provide clear analytical data.
  4. Automating data analysis processes:
    • Optimizing data import, processing, and reporting to enhance efficiency and accuracy.
The Results:

The implementation of the data visualization system led to significant improvements in financial data management and analysis within the company. Key results include:

  1. Increased data visibility:
    • Users could easily access and interpret complex financial data through intuitive graphical representations.
  2. Improved decision-making:
    • Detailed analytical data provided by the system facilitated better financial planning and decision-making.
  3. Enhanced efficiency:
    • Automation of data analysis processes and data validation in files helped eliminate errors, leading to faster and more reliable results.
  4. User satisfaction:
    • The user-friendly interface and reliable system functionality were highly appreciated by the staff, significantly increasing productivity and engagement.
TECHNOLOGIES:

NET MVC

jQuery

MSSQL DB

Entity Framework

AWS S3

RabbitMQ

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