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What is Data Skew in Salesforce?

Today, there is incredible growth in the usage of data, and we are running out of storage space as a result of the enormous volume of data. This causes significant performance degradation and long-running procedures, both of which are undesirable. Day by day, this pace quickens, and we're gradually getting to the point where we won't be able to handle the data, hence this situation in Salesforce is called a Data Skew.

In this blog, we will talk about the following topics, which are listed below:

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What is Data Skew in Salesforce?

Data skew in Salesforce is a phenomenon that occurs when the data in a certain Salesforce organization is heavily concentrated in a small number of records.

It is a common issue that companies experience in their Salesforce organization because of the way Salesforce stores data.

When data is stored in Salesforce, it is organized within objects and records, and each object can have many records.

As companies use and update their Salesforce organization, the number of records in each object can increase and sometimes become imbalanced.

This means that one or a few objects can contain a disproportionate amount of records, while other objects contain very few records.

Data skew can cause a number of challenges for companies, including decreased performance, increased system complexity, and increased cost.

When data skew exists, it can take much longer time to execute operations on the Salesforce platform, and it can be difficult to manage the data.

In addition, the data skew can increase the cost of running the Salesforce organization because more resources are being used to store and process the data.

To reduce data skew in Salesforce, companies should regularly review their organization to identify any objects that contain a disproportionate number of records.

Companies should also consider implementing strategies such as object consolidation and data archiving to reduce the size of their organization and help keep the data balanced.

Additionally, companies should review their existing data policies and consider making changes to help ensure that data is entered and stored accurately.

Data skew in Salesforce can be a challenge for companies, but with regular reviews and the right strategies in place, companies can reduce the amount of data skew in their organization and ensure that their data is properly balanced.

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Types of Data Skew

In Salesforce, there are three different sorts of Data Skew, each with a different set of duties and playing a crucial role. Let’s look further to understand the various forms of Data Skew in Salesforce.

Types of Data Skew
  • Account Data Skew

Account data skew in Salesforce is a common problem faced by many organizations. It occurs when one or more users are creating, updating, and deleting accounts at a much higher rate than other users.

This can lead to data being skewed, which can cause performance issues, incorrect reporting, and other problems.

Account data skew can be caused by a variety of factors, such as users working on a single account for an extended period of time, or users creating accounts with a high frequency.

In addition, it can also be caused by incorrect application settings or data entry errors.

  • Ownership Data Skew

Ownership Data Skew in Salesforce refers to an imbalance in the distribution of record ownership among users within an organization.

This occurs when a disproportionate number of records are assigned to a single user or a small group of users, resulting in a skewed distribution of data.

The issue of Ownership Data Skew can arise for various reasons such as a lack of proper allocation of records, a high volume of records created by a single user, or an imbalance in the distribution of work among team members.

This can lead to several problems, such as data accuracy, difficulties in sharing information, and an increased risk of data loss in case of a user leave the organization.

  • Lookup Data Skew

Lookup data skew in Salesforce is a common issue faced by organizations using the platform.

It refers to an unequal distribution of data in a lookup relationship, which can cause performance problems and limit the functionality of the system.

The issue arises when a single record in a lookup relationship is related to a large number of records in another object.

This can lead to an excessive number of database transactions, slow performance, and even cause system crashes.

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Ways to avoid different types of Data Skew

There are a number of ways to avoid the impact of Data Skew since it adversely affects long-running processes and system performance, but we need to be aware of the most effective ones. The following strategies may be used to deal with different forms of Data Skew:

  • Account Data Skew Solution

To assist prevent locking and performance difficulties, we should always aim to avoid account data skew scenarios. Here are a few tactics for minimizing problems caused by account data skew:

  • In order to lower the record-level obstacles, we can redistribute the child objects if the skewed accounts are present.
  • Redistribute child objects in batches for skewed accounts at non-peak times to lessen the effect of record-level locking.
  • To prevent sharing recalculations for skewed accounts, think about using a Public Read/Write sharing architecture.
  • Ownership Data Skew Solution

Ownership Data Skew Solution can be done in Salesforce by following the numbers of points which are as follows:

  • After each batch of 10,000 records or data objects, assign ownership to various users.
  • The distorted owner (Owner of a record) should ideally not be involved in any way.
  • When a position is required of the skewed owner, it should be at the top of the hierarchy inside its own branch of the role hierarchy.
  • Avoid storing them in any open groups that can serve as the basis for sharing guidelines.
  • Lookup Data Skew Solution

In Lookup Data Skew there are two ways to reduce the data skew, let’s discuss them one by one in detail:

  • Time-Saving Record Reduction:

A better end-user experience may be had by improving record-save performance since it shortens lock times, which decreases or eliminates lock failures.

  • Extending the distribution:

The main cause of lookup skew is that several records look up to a single record, which is the problem. To remedy the issue, we can disperse the skew.

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Conclusion

We really hope that this blog helped you to fully understand the Data Skew in Salesforce. We attempted to cover every area of Data Skew, including its explanation and remedies. Since Salesforce is the most well-known profession in the IT industry, you shouldn’t wait and think to start your career. Instead, do it right away as Salesforce is an evolving field and it will be beneficial for your bright future.

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