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CommunityCategory: QuestionsHow can ILM Assessment SE help address data growth challenges
Anonymous asked 4 years ago
I’m wondering how the new ILM Assessment offering can help companies. What are the pros and cons of this tool when it comes to addressing data growth challenges?
1 Answers
Best Answer
webadmin Staff answered 4 years ago
Solix EDMS Database ILM Assessment Standard Edition (SE) plays a significant role to assess the amount of archive eligible data in a given database based on business criteria. There is also a provision to depict the number of rows with corresponding data size of archive eligible data in a pictorial representation.

Solix EDMS Database ILM Assessment Standard Edition (SE) is integrated with retention management feature that helps to assess the archive eligible data based on the retention policy defined. Once retention policy is assigned the data assessment and data assessment get executed, thereby the data found before the specified retention date based on the specified retention period will be assessed for eligible data. It also analysis data growth yearly and depicts the statistics data growth of business in graphical representation in dashboard.
The three types of data assessment:
1. Database Size Snapshot: Assess the data distributed in schema’s, database size and size of Top N tables.
2. Module Level Archive Eligibility: Module-wise data assessment will be carried out to assess the archive eligible data.
3. Data Growth Forecast: Analysis the data growth of business that helps to forecast the future data growth in business.  Data growth analysis is categorized into two types, they are: 
Table Level Forecast: Enable to analysis the data growth of business within given period based on table level data and forecast the future data growth in business. 
Database Level Forecast: Enable to analysis the data growth of business within given period based on database level and forecast the future data growth in business. (Make sure that the atleast once the database size snapshot must be executed to forecast the data growth.)