Salesforce – Page 2 – Puneet Khosla

Create a Dataset with CSV file

Lets start creating the first dataset (you can read more about dataset in my blog on Datasets – Click Here) using a CSV file.

STEP 1 : Click on Create Button & Select Dataset

There are multiple ways to start creating a dataset. After entering Analytics Studio, you can either click on the “Create” button (on the top right corner) or you can go into your Einstein Analytics app and click the button, etc. Select Dataset.

STEP 2 : Choose Data Source

Choose CSV File as we are creating dataset from csv.

STEP 3 : Upload the CSV File

Upload / Drag and Drop the csv file to upload. Here we are uploading Opportunity Data. I am using the data available in my org (built as part of one of the trailhead modules)

STEP 4 : Define the properties of the Dataset

This is the place to give the name and the App where you want to save the dataset. You can also check the file properties (Auto detected) in case it needs a change. Data Schema file will be covered in later blogs, however the file (also known as Extended Metadata or XMD file) is used for some formatting options of the dataset fields and their values. Click Next button to move to the next step.

STEP 5 : Preview and Edit the Field Attributes

This step now allows you to preview the data being loaded and to change any settings. This is the step where you define the type of column (Dimension, Measure and Date) and set its attribute. By default Einstein Analytics automatically detects the data type but you can change it as well.

In this step, you can check the fields that would be part of the dataset. As we can see we have Account.Name, Amount, CloseDate, Id, etc. as the columns (or fields) of the dataset.

You can preview the data getting loaded. Here I have a screen of 3 columns, where we will now make some changes.

We have a column as Account.Name. This is because in Opportunity Data, we also extracted Parent Account’s Name field and in the csv it got extracted as Account.Name. Further to note Analytics Studio automatically picked the field as dimension (qualitative value).

You can choose to fix column name in CSV file before loading or you can change the field label in this Step. So now we will change Account.Name to Account.

The Next field to check is the Amount field. This field is auto-detected as a Measure (value) field as the data in this column is numeric.

Since its a currency, we will change the number format to 0.00. Furthermore we will add a grouping symbol and a Decimal Symbol to our data.

We will now check the Close Date field. This field is of type Date which has been auto-picked by Einstein Analytics.

After doing checks / changes to the attributes of the fields, we move to the next step.

STEP 6 : Einstein builds Dataset

This is where Einstein Analytics Engine builds the dataset. It can take a few seconds for the while to load. Though I like the page as we can see Mr. Einstein doing the magic.

STEP 7 : Review the prepared Dataset

Once the dataset is loaded, you will automatically get transferred to the dataset page. There you can check your dataset properties and also add Security predicates and XMD file. A good check here is to check the number of rows loaded.

You can even the view the dataset data by clicking “Explore” button. This opens a Lens where you can add your filters, bars (or the dimension) , bar length (measure or calculation on measure)metc. and choose a chart to display.

I added a filter saying Account contains “Einstein”. Bar Length has been kept as Sum of Amount. Bars have been kept as Closed Date (Quarter) and Account (and not Account.Name). Just to add, we only loaded Closed Date, however Einstein Analytics provided us with various groupings like Year, Quarter, Month, Year-Month, Year-Month-Day, etc.

We will soon use this dataset in our dashboard.

What is Dataset in Salesforce Einstein?

A dataset is simply a collection of rows and columns. If you have used Excel or Google Sheets, then one dataset is one worksheet. If you have built databases, it is one table.

Column of the dataset indicates various fields. Rows of the dataset indicates various records.

A dataset can contain the following type of data

Dimension
Measure
Date

Dimension is a qualitative value / text / a field that you want to group your data with / measure your data against / use it as filter eg: City Name, Status, Salesperson, product number, etc. A number (like Product Number) can also be a dimension as the number represents something you can group by. In a Lens (Chart) Dimension is used in Bar & Filter.

Measure is a quantitative value / number / a field that gives actual value eg: Amount, Number of Cases, etc. While creating the dataset, it is important to identify the value fields and ensure that the column is marked as Measure. A measure can further be aggregated (like Count of Rows , Sum of Rows, etc.). In a Lens (Chart) Measure is used in Bar Length & Filter.

Date is used to denote Date fields in Dataset. If we mark the column as Date, then it helps in analysis by automatically allowing the grouping / filtering by Days, Months, Year and also Relative Dates like Last Week, Last Month, etc. In a Lens (Chart) Date is used in Bar & Filter.

Once the dataset is setup and ready to use, we can then build various charts and dashboards on top the datasets to provide useful analysis and insights for the business.

Salesforce Einstein : Is it for me?

Salesforce Einstein – In Salesforce world, this has a created a buzz. Salesforce Einstein is a big thing. It combines the power of Analytics and AI.
The big question that comes to your mind, should I really know and learn about Einstein?

Person 1 : I am an expert in Apex / Aura / LWC. Do I really need to know about Einstein Analytics or Discovery?
Person 2: I am an expert Admin. I can do amazing things with Flows, Process Builders, Layouts, etc. I can’t write code. Do I really need to know about Salesforce Einstein?
Person 3 : I am a consultant. I know Sales Cloud, Service Cloud, Community, FSL. Should I know about Einstein?

As per me, for the above scenarios, the answer is “Yes” .. Really !!

Before I talk about Salesforce Einstein features, its really important to understand why I should invest my time in knowing about a certain technology and how it impacts my day to day work.

Salesforce is one platform that is continuously growing and innovating at a rapid pace. In my career, I started with Admin work, Learnt Apex, then Aura and LWC. Along with that I am also enhancing my knowledge in Einstein .

Let’s say we have a brand new org and we need to make it functional for user(s).
First we try to do everything out of the box and basic for users to be functional as soon as possible.
Once they start using the system, we build fancy UI (Developer’s delight) and automation.
Then we bring other systems together on one platform.
Then what : We continue to innovate and enhance.

However at the same time we are also building a very crucial thing – Data.

Data plays an important role in our day to day role by providing analysis of what we have done so far, what we are currently doing and what better we can do in future.

Now with large amount of data we have (Salesforce or other systems), how do we Analyze it / how can we use the past experience to build a better future?
The answer is Salesforce Einstein.

Do we really need a tool to analyze / predict – Why can’t my Dev team just run some queries and put some logic into it?
May be 100 records, they can do it minutes. 1,000 records may be hours. 10,000 records – Days? Can you really wait for days?
Now think about what if there are 50,000 records?

What if you no longer need to wait for IT to provide all this and can access powerful data insights on your desktop browser or mobile.

Welcome to the world of Salesforce Einstein. A place where you can easily build Dashboards to visualize data and share insights (Einstein Analytics). A place where you can use the power of machine learning, AI and statistical Analysis (Einstein Discovery).

So is Salesforce Einstein replacement for a Dev / Admin / Consultant ? Consider Einstein as your Friend, Adviser , Additional Team member who will provide you powerful insights to help in day to day work.