In the previous section we discussed about the various proactive measures that we can take to ensure
that the incoming data into Salesforce whatever the data that is coming into Salesforce that is clean
and productive.
So while for that we discussed about of the various strategies because prevention is always better than
cure.
So then we handle the incoming data.
That in itself solves half of the problem so that internally we disclosed in the previous section in
this section we are going to discuss about the reactive measures meaning how do we clean up the existing
data that does then and sales force.
So reactive measures when we say reactive measures.
It also means cleaning up the existing data.
And it also means as the measures to ensure that the data quality is maintained in the system meaning
regular maintenance.
So it is just not sufficient that we clean up the data.
It is also necessity that we maintain the data quality in the system that does regular monitoring.
So where did all the reactive measures that we take that can be used for cleaning up the existing data.
And once we clean up the existing data how can we maintain that data.
How can we maintain that quality of data.
So those are the active measures we will be discussing in this section.
So first comes the data quality of reports and dashboards.
Then we talk about merging that our guards and then we'll talk about the mass deleting records and then
we'll also talk about how to optimize the data was a beauty structure.
And finally data scoop.
So in this section we'll talk about data quality reports and dashboards.
That is a very first one.
So what does the main objective of these data quality reports and dashboards plus a confidant an audit
and you already have data in that.
And we want to clean up the existing data data sets us.
OK so now then we want to clean up the data.
First we need to understand the current state of the data.
Right.
So among the data among the 100 percent of the data.
How much is good data.
How much is bad data.
How much data is incomplete.
How much data is not used.
Right.
So first we need to analyze the existing data.
One only when we analyze the existing data only we get that information.
Then we can take appropriate actions to work on those bad data.
So first we need to get that analysis because as a senior admin you want responsibility for maintaining
good quality data in your system.
We need to actually had the customers use Salesforce and into some good data in the system.
Legendary in many ARGs of the thing is up the business process.
We have different to several teams and it might be really complex a coordinating with several teams
right alike.
There may be several departments in your business and each department that they may have a data on process
of creating and maintaining data like you know like all departments.
Basically they may need a customer contact information but each department may have the intellectuals
of information for that customer data sales.
May use Salesforce accounting may have a some different system of spreadsheets and everything.
Customer support they may not even have any system at all.
We don't know.
So every department might have their own processes also maintaining data.
They are in process of using data.
So it really becomes complex.
So when we want to analyze the data quality we need some measures.
We need some tools to analyze exactly how the data quality is it not always efficient for us to save
the necessary data.
Say for example leads it leads may need a name company email address phone number and will revenue at
all and territories may need to set a different set of data.
Customers a bit maybe a different set of data.
So just not about the necessary data.
It is also about some other factors that basically gives us data quality.
So what are all the different factors that decides the Data Quality listed here are some of the attributes
that go on to build the data quality.
First comes age it means when was that data when was that a card.
He asked.
Modified so that will tell us the age.
So what percentage of records have been updated recently.
So we need to assess that information so that will give us an approximate percentage of the records
that are being updated regularly and that are being used in a regular basis.
So that does age next US completeness meaning is our data complete are on key business fields on records
filled in because you know you can't find upside opportunities without complete a company hierarchy
and industry information.
So completeness is also very important.
So how do we analyze the completeness of a record.
We need to list the fields required for each business use and once we list on the fields that are required
we need to run a report that shows the percentage of blacks for these fields right.
So that does all we get analyzed completeness so we can know how much percentage of records is complete
and how much percentage is incomplete.
So this is the second attribute that God attributes to data quality the thought I attribute this accuracy
how accurate is your data.
Your data may be complete but is it accurate.
Has it been matched against a trusted source.
So that is accuracy of data accuracy of data is also important and that this maybe you can analyze using
some data quality apps from App Exchange and then comes consistency meaning is a data consistent.
Does it have the same formatting spelling and language used across it at cards.
That is called this consistency the formatting of records the language used across it at cards.
Is it consistent across all direct cards.
So that does consistency and how we evaluate consistency.
They can definitely run reports began to report that shows that values like a date currency state country
region feels and we can find the variations we can find how many variations are used to for a single
value say for example state California it can be a California.
All right so there can be variations for a single value so begin to run the report and find out the
percentage variations so that does call this consistency the record consistency across the ARG next
is duplication duplication we very much know duplication again like it is inefficient and it gives no
use absolutely nothing for the customer absolutely nothing for the business as well so absolutely duplicate
data means inefficiencies so we need to find out how many how many duplicate records that existing another
ARG and how do we do that we can use that duplicate management features in Salesforce we discussed that
in the previous section you can use matching rules that duplicate rules and you can run duplicate jobs
on a regular basis and you can also install a duplicate reduction app from app exchange you can take
help from those apps and for handling these duplicate records and finally use such is the data in the
system is really being used.
Is it really any use to the customer and how do we analyze this.
You can have it.
You can use the several tools and resources that your business uses and you can understand.
Are you really optimizing the data I use.
So basically these are the several factors.
These are the several attributes that contribute to your data quality.
So you need to consider all these attributes before you decide on these my data quality really good.
So how do you analyze these attributes.
Right.
You need a means of analyzing these attributes.
Now that we know the significance of these attributes.
Yes but how do we analyze these attributes and how do we find out if these attributes really make a
difference.
One way.
Definitely yes.
You can have your own custom reports on dashboards that is built using the custom fields from several
objects that is pulled in and you can create your own custom reports and dashboards and use it for your
business and analyze all this criteria.
Definitely yes.
But that is under the efficient working on for this.
That is using the data quality analysis dashboards.
It does an app exchange package and that is readily available and it is free.
So why not try that.
Right.
So go to app exchange and look for this data quality analysis dashboards app.
This is definitely a very efficient app that helps us to analyze other data.
And it's free of cost estimate.
So please go ahead and install this app.
And this gives us a reports on dashboards for assessing other data quality is just installed the way
you would install it.
Your regular app click on get it now installed in your app click log in and I give you the address and
skills developer credentials once you give your credentials.
It will ask you for which I'll use us.
This is mainly fragments.
So let's install fragments install
installation complete pull effect click done awesome so answer install the packages you should be able
to see your data quality analysis app.
OK so the package is installed now and how do you access that.
So this is basically reports on dashboard so right.
So I reports on dashboards to your tabs is not available
reports dashboards.
OK and go for dashboards
and you should be able to see these data quality apps
to look at this.
This is cool right.
See you like we were able to install that in a second.
And how much this reports on dashboards would be useful to us.
We can assess of a data quality and if you go to the dashboard you can see the columns context and opportunity
data quality and you also have campaigns leads and activities
which really come up in a minute.
Here it is you have cases and contracts
he it is and you have high level data quality analysis
awesome.
So basically that are a separate dashboards for the objects like you see the accolades context and opportunities
campaigns and leads.
This is for cases this is this gives you a high level data quality analysis basically tells you the
percentage like how good is your data say for example the actual data quality is this much and the context
is even more good opportunity not that much.
And campaigns which tilted is in the green for activities that may not be any activity records at all
in the system.
So basically these dashboards give you a very good idea about what the zero data quality.
You can also check out the other dashboard
and you can see what all the factors that it's based on based on industry rating type phone and complete
address.
Right.
You can see those factors.
You can click on them if you want to access the report behind that right click on customize
so that will give you the report behind that so definitely this is your step one.
When you start analyzing the quality of your data.
So if your business in your business if you have bad data if you start a data cleansing the first step
would be to analyze the data.
Right.
Only then we can take appropriate actions.
So for analyzing the data there's a data quality of reports on dashboards.
Definitely some must do.
So goal install this app and understand your data and then we'll think about the appropriate actions.
So this is about using this app data quality reports on dashboards installing that package and getting
benefitted out of that.