Why do I get Bad Salesforce Data?

Salesforce data

Why do I get Bad Salesforce Data?

Salesforce data

In your childhood, did you ever make the mistake of copying a math question wrong, and then feeling good that you got the correct answer according to the copied question? Well, no matter how good it felt, the answer still wouldn’t fetch you marks in the examinations, regardless of how many steps you showed.

Well, that’s what happens when you start work with wrong data.

If you are using Salesforce for quite some time now, you likely would have gone over bad data. Wrong close dates. Wrong Opportunity stages. Wrong project statuses. Information missing from a large portion of the fields on your custom objects. It’s a wreck. We get it.

At the point when a business utilizes bad information, expectations are missed. Bad data ruins your Salesforce customer relationship management strategy, clients aren’t reached in a convenient way, and you lose out on retention when the clients aren’t serviced properly. What’s more, when projections are made based on bad data, it is bound to cause havoc in achieving your projected target metrics –  causing a negative chain response in the business cycle, particularly for trading on an open market platform.

All in all, how does wrong information get into your SFDC in the first place? This is straightforward if we consider what is influencing the data through the span of its life cycle.

What Affects Your Salesforce Data Quality?

There’s no need to wreck your head in pinpointing your source of frustration. There’s a limited number of things that can influence your Salesforce information for the duration of its life. These are external sources of data, automation that follows up on information, and information administration forms. In the event that you have a data quality issue, you have to take a look at how any of these three things are influencing information all through the data lifecycle in your Salesforce organization.

Understanding The Data Lifecycle

You will realize that the data lifecycle is your closest companion when you break down information quality issues. Taking a close look at what happens to the data in Salesforce is precisely how a well-informed salesforce pro would approach solving the problem. It’s a straightforward and organized approach to deal with the wreckage.

The data lifecycle can be thought of simply like the life of a butterfly. It starts with creation, changes for the duration of the time it exists, and finishes (let’s not kill the poor butterfly) towards the end of life. In specialized terms, we call these progressions that influence the condition of information during its life cycle “CRUD”, which despite the fact that it sounds messy, it’s most certainly not. It just stands for ‘Create’, ‘Read’, ‘Update’, ‘Delete’.

Let’s have a quick run through of each aspect

Creating Salesforce Data

In Salesforce, records are made almost constantly. It can be done by utilizing external data sources through integrations, importing lists.automation or administrative data management processes. In fact, each of these techniques has a common similarity – hidden away in the background, an ‘insert’ function is executed in the Salesforce database.

Reading Salesforce Data

Whenever someone needs to see a record, whether it’s pulling up a record detail page or taking a look at a record in a report, they are said to be reading data. In specialized terms, it is the point at which a “select” command is executed in the Salesforce database. Reading information doesn’t straightforwardly influence information quality since nothing is going on to the record while it’s read, but it is important in helping the users make decisions when they are editing or deleting Salesforce data.

Updating Salesforce Data

Whenever somebody says they are altering a record in Salesforce, in the background, that activity runs an “update” command against the Salesforce database. Refreshing or altering Salesforce data can occur in any of the situations created in the “Making Salesforce Data” segment above. For instance, in a data administration process, a client can refresh a record not long after she made it.

Deleting Salesforce Data

When you remove a record in Salesforce, you actually perform a “delete” action in the Salesforce database.

Automation and integrations (e.g., a trigger in Salesforce that erases a record) can erase Salesforce data. Nonetheless, these occurrences are usually not that frequent when they make or refresh information. Erasing information will probably occur in a manual information administration process in Salesforce, however, there are ordinarily limitations set up to keep clients from erasing information in bulk.

So What’s This All Got to Do with Data Quality?

Now you know in what ways your data is influenced during its lifecycle. As such, information gets created by one means or another, experiences numerous alterations through its lifetime, and later, it gets erased. In the event that you have an information quality issue, you simply need to search for issues where information is getting created, refreshed or erased in a way it shouldn’t. Organizing your analysis of data quality along these measurements will help make managing your information quality issues appear less frightening and cumbersome.  


What issues do you face frequently while you use Salesforce? Let us know in the comment section below.

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