Salesforce Data-Architect Exam With Confidence Using Practice Dumps

The three characteristics of a Skinny table that help improve report and query performance are: Skinny tables can contain frequently used fields and thereby help avoid joins. Skinny tables are kept in sync with changes to data in the source tables. Skinny tables do not include records that are available in the recycle bin. These characteristics are beneficial because they reduce the query complexity and execution time, and improve the data accuracy and freshness. For example, skinny tables can contain frequently used fields from multiple objects, such as Account and Contact, and thereby help avoid joins that can slow down queries4. Skinny tables are updated automatically when the source tables are modified, so they always reflect the latest data5. Skinny tables do not include records that are available in the recycle bin, so they only contain active records that are relevant for reports and queries.

Using leading % wildcards, performing large loads and deletions, and using NOT and != operators are three options that prevent a query from being selective. These options can cause the query to scan a large number of records or indexes, which can negatively impact the performance and scalability of the query5. Using a custom index on a deterministic formula field, on the other hand, can improve the query selectivity by allowing the query to use the index instead of scanning all the records6.

The three activities that will be required to identify a successful master data management strategy are:

Identify data to be replicated: This activity involves determining which data elements need to be copied from one system to another, and how frequently the replication should occur. This can help ensure data consistency and availability across systems.

Create a data archive strategy: This activity involves defining how historical data will be stored, accessed, and deleted over time. This can help optimize data storage, performance, and compliance.

Define the systems of record for critical data: This activity involves identifying which system owns and maintains the authoritative version of each data element. This can help avoid data conflicts and duplication across systems67.

Install a data warehouse is not a required activity, but rather a possible option for consolidating data from multiple sources for analytics purposes. Choose a Business Intelligence tool is not a required activity, but rather a possible option for visualizing and reporting on data from various sources.