Deep Analysis Tool - Use Case

Article Summary

This article provides detailed comprehensive information on Deep Analysis and step-by-step instructions for performing the analysis.

Deep Analysis Tool (Business Transaction Impact Tool)

The Deep Analysis Tool in OvalEdge provides invaluable insights by identifying impacted data objects across different data systems when a business transaction occurs in one or more enterprise applications. This analysis is particularly useful for understanding the flow of information specific to a business transaction or use case, leveraging profiling metrics of data objects captured in a controlled setting.

Follow these steps to identify transaction-related data objects:

Restrict Concerned Applications:
Ensure that the concerned applications are restricted for generic use, allowing focused analysis.
Baseline Profiling:
Perform profiling of the connectors of the data systems for the applications. This establishes the baseline metrics before the business transaction.
Perform Business Interaction:
A user performs the desired business interaction on the enterprise application(s).
After Transaction Profiling:
Conduct profiling of the connectors of the data systems again. This generates profiling metrics after the completion of the business transaction.
Comparison and Analysis:
Compare the before and after profiling metric sets. Any data objects whose profiling metrics have changed are potential candidates related to the business transaction.

The information obtained through the Deep Analysis Tool is invaluable for understanding the impact of business transactions in complex enterprise environments with multiple integrated applications.

Note: Prior to utilizing the Deep Analysis feature, it is essential for the schema under consideration to undergo profiling at least once. This prerequisite ensures the availability of necessary profiling data, facilitating accurate comparison of metrics and yielding reliable and meaningful analysis results.

Use Case: Performing Deep Analysis

A company XYZ Corp wants to perform a deep analysis of their Information_schema, which contains information about their products and stock levels. The goal is to gain insights into the products and stocks that will be impacted when a new transaction is made. The following steps outline the process for achieving this objective.

Initial Profiling: Before using the Deep Analysis feature, ensure the schema has been profiled at least once, providing necessary data for accurate comparison and evaluation of changes.
Enabling Deep Analysis Tool: In the administration > System Settings > Others tab> key"enable.deepanalysis" option set the parameter to true to display the Deep Analysis sub-module in the Advanced Tools section.
Accessing Deep Analysis Tool: Navigate to Advanced Tools > Deep Analysis Tool to access the feature.
Creating a New Deep Analysis: Create a new deep analysis, such as "Analyzing Inventory Schema," to analyze specific schemas.
Adding Schemas: Select the ‘Information schema’ from the My-Sql-A connector to run the deep analysis. You can select multiple schemas to analyze the data changes of that particular schema. Once the schemas are selected, click the 'Identify Impact' button to initiate a background job.
Change Detection: Ovaledge's deep analysis performs an advanced job in the background, comparing current profiling results with the initial profiling data to detect any changes that have occurred in the schema. This includes additions or removals of tables, alterations in structure, and modifications in column attributes. Once the job is successful, the results can be viewed in the Table Change Summary and Column Change Details.
1. It provides a clear overview of the detected changes. In the Table Change Summary, the status of each table is indicated, highlighting the number of rows that have been added or deleted such as "xxx Rows added" or "xx Rows deleted". This information is presented in the remarks column.
2. The Column Change Details provide more granular insights into the modifications made to individual columns. Any data additions or deletions within specific columns are displayed in the remarks column, displaying the corresponding number of rows affected.