Today's world is stacked together on the basis of different constructive data. In terms of high-level institutions, we are just another file where our databases speak on our behalf. Hence, we know that our data is crucial, and therefore we need to shield it against any data mismanagement mishap that may occur: like data loss due to system hack or erasing of data through crackers.
And what could be more data security promising than customer relationship management (CRM)? But could you even wildly guess the costs of CRM solutions for data security before salesforce came into the picture, well it would cost around millions of dollars? Yes, can you imagine paying millions of dollars for a mere backup program and then miserably failing to carry it out, sounds dumb isn't it, but it wasn't because nobody had any choice?
It was then that Salesforce emerged to rescue companies from burning stacks of money into CRMs. Salesforce developed the concept of simple backup with a lot less money that we today know as the cloud computing system.
In short, Salesforce revolutionized the backup models of companies by emancipating them from long term contracts, enormous amounts of fees, costly license maintenance, and, most of all, complicated working mechanisms. With Salesforce, the customer could pay a mere 50 dollar fee for cloud computing subscription, thereby evolving the methods of manual data backups through data models like MoveData NPSP.
As we highlighted, the backing up procedure is now effortless, then let us illustrate the tops you might want to follow while importing your data to the Salesforce cloud computing system.
Carefully Scrutinize The Data For CSV Files
CSV files function differently from other files. These files run around the concept of commas. They stand for Comma Separated Values, thereby implying that data after the punctuation comma should be immediately imported to the corresponding next cell. Hence, commas indicate a shift; each comma would introduce the value that falls after it until it encounters another comma.
Therefore, we need to do thorough checkups before importing; otherwise, our data might end up in the wrong field.
Check For Redundant Files Before Importing
Redundant files are not harmful in any way, but they will inevitably end up taking up data space. Import wizards would indeed check and present you with duplicate data before importing. Still, it would be better if you manually erase redundant files as that will leave no trace of duplicate data, and you will have substantial storage for your future data projects.
For these processes, you might want to work for Excel, as Excel swiftly identifies redundant data, making the redundancy quest easier and smoother.
Look Out For Common Pitfalls Regarding Picklists and Similar Street Avenues
A new update in Salesforce enabled the country and state field to picklists form, which initially used to be Text fields. Therefore, now while dealing with state and country names, we need to match the exact names that are mentioned in the picklists; otherwise, Salesforce might end up rejecting your record.
Now, if we talk about address filling, we know that the street field in Salesforce is made up of multiple components: address, landmark, street name, and postal codes. We know that street criteria are available to us in three fields that vary in name in different versions of systems.
Therefore, we know there might be similar names of streets for different people, and hence we need a detailed address in three fields to combat any similarities that might arise. The most unique of all is the postal address that separates all the address records from one another. Therefore, similar street names should be differentiated by postal codes for maintaining proper data records.
