Infitar It Solutions

14/12/2024

I am Abdul Kader, a seasoned Zoho Developer with nearly a decade of experience, delivering tailored Zoho solutions since 2015. My expertise spans the entire Zoho ecosystem, with a primary focus on Zoho CRM, Zoho Books, Zoho Inventory, Zoho Billing, Zoho Desk, Zoho Analytics, Zoho Data Prep, Zoho People, Zoho FSM, Zoho Flow, Zoho Workspace, and Zoho Creator. Proficient in developing custom applications, process automation, and advanced integrations, I provide end-to-end solutions to streamline business operations and enhance productivity.

I specialize in Zoho CRM customizations, workflow automation, and integrations with other platforms using tools like Make.com. My extensive experience includes designing systems to automate workflows for eCommerce platforms like Shopify, Wix, and Squarespace, as well as creating custom modules for CRM applications.

I am known for delivering results-driven solutions and collaborating with clients across industries such as accounting, digital marketing, and law firms. My availability is tailored to clients in both Indian and EST time zones, ensuring timely communication and support.

In addition to my technical expertise, I have a proven track record of providing exceptional customer service and working seamlessly with teams across the globe.

22/08/2023

As a field service business owner, do you find yourself struggling with productivity and profitability? Does most of your time go in paperwork and phone call...

12/07/2023

5 key practices for building informative analytics dashboards
https://www.zoho.com/blog/analytics/5-key-practices-for-building-informative-analytics-dashboards.html

In this blog, we outline five key practices for building informative analytics dashboards. By following these steps, BI users can transform dashboards from being a mere static chart aggregator into a powerful tool that empowers decision-makers.

16/02/2023

❇️ ❇️ Change data type In ZOHO DATA PREPARATION ❇️ ❇️

Zoho DataPrep automatically identifies the data type of each column in your dataset during the time of import.

Sometimes due to multiple errors in the dataset, DataPrep may not correctly identify the data type, in which case you can manually override to change the data type of the column using the Change data type transform.

🔶To change the data type of a column

1. Right-click the column name and select the Change data type option from the context menu.
2. The Select datatype dropdown in the Studio panel shows a list of datatypes with match accuracy.
Match accuracy is the percentage of data volume in the selected column that conforms to a data type.
3. DataPrep supports the following data types:
• Text
• Number
• Decimal
• Timestamp
• Positive number
• Date
• Date time
• Time
• Duration
• Currency
• Length
• Temperature
• Boolean
• Email
• URL
• List
• Map
• Percentage
4 . After selecting the datatype, choose the desired format from the available options. Click here to know more about the format options.

Zoho DataPrep uses the format specified by the user to identify
if the column data conforms to the data format specified and marks the column data as valid or invalid.

5. Enable the Add constraints toggle to set constraints and determine valid values in a column. The values that do not follow the constraints you have set will be categorised as invalid values in the column. However, they will not be removed. Click here to know more about constraints.

6. If you want to set a column as mandatory, y ou can select the Set as mandatory (not null) checkbox.

7. You can also apply this transform along with constraints on multiple columns. Select the required columns using the icon under Columns to apply .

8. Choose a datatype from the listed types and click Apply .

9. You can also create your own data type by choosing Create custom data type option.

🔶To add a constraint
1. Enable the Add constraints toggle.
2. Select an option from the constraints section and enter the string. The options are displayed based on the data type of the first column you have selected in the Columns to apply field.
3. When you add more than one constraint, the logical operators, AND or OR appear next to the constraints. You can click to toggle the logical operator between AND and OR.

🔶Criteria expression

Using the logical operators, you can combine the constraints and apply logic to determine the rule of precedence. The final expression is displayed in the Criteria expression box. You can click Edit to alter the default expression using logical operators and parenthesis to specify the precedence or the sequential order as to which constraint should be evaluated first. Click Save after making the required changes.

4. Click Apply .

🔶If you select the Date, Datetime or Time types
You can select the required tiles and construct the Date, Datetime or the Time format.

1. Click to select the different date and time components to build your custom format.

2. You can choose the 24-Hour format by selecting the hour-format icon which would appear at the right end when you hover your mouse over the text box.

3. You can click on the grip portion of the tile (grip icon that appears on hovering your mouse over) and move around the tiles to rearrange them.

4. A live preview of your date, datetime or a time column is shown as you build your format.

The date, datetime or the time format constructed is invalid if one or more of the following conditions are not met:
• You have to choose at least one tile from the Day, Month, and Year tiles.
• You can use the characters, 'Z' and 'T' only once in a datetime and a time format.
• The tiles that follow the character, 'T' must be related to time such as Hours, Mins, Sec.
• A datetime and time format must contain an Hours tile.
• In a datetime format, you can use either the character, 'Z ' or any one of the T.zone tiles.
• You can use any one of the T.zone tiles in a time format.
• You can choose only one format from the Day, Month, Year, Hours, Mins, and Sec tiles.

DataPrep allows only the following delimiters while constructing a date or a date-time format.

Date and Datetime delimiters
/ : - , . \s T Z
Time delimiters
/ : - , . \s Z

09/02/2023

❇️ ❇️ Create buckets – Date (ZOHO Data Preparation) Part-5

You can classify a group of date values or individual dates using the bucketing technique.

The bucketing options for a date column are:
• Weekday or not
• Month of the year
• Week of the year
• Week of the month
• Day of the year
• Day of the month
• Minute of the hour
• Time of day
• Custom date range

🔷Day of the month

This option lets you create a new column next to the date column to classify the days in a month.

To apply the Day of the month option to a date column:
👉Right-click the date column in the Operations page.
👉Select the Create Buckets option from the context menu.
👉Select the Day of the month option from the Select bucket option dropdown in the Operations panel.
👉Enter a name for your new column in the New column name field.
👉Choose one of the options in the Create buckets using section and fill in the required fields (see detailed descriptions below):
• Custom range
• Specific values
👉Click Apply .

🔷Custom range

You can use the Custom Range option to input the conditions to determine bucket labels.
👉To do this, enter conditions using these comparative operators:
• Equal to (=), more than (>), or more than or equal to (>=) as part of the Start condition
• Less than (

09/02/2023

❇️ ❇️ Create buckets – Date (ZOHO Data Preparation) Part-6

You can classify a group of date values or individual dates using the bucketing technique.

The bucketing options for a date column are:
• Weekday or not
• Month of the year
• Week of the year
• Week of the month
• Day of the year
• Day of the month
• Minute of the hour
• Time of day
• Custom date range

🔷 Minute of the hour

This option lets you create a new column against the date-time column classifying hours of time in a day.

To apply the Time of Day option to a date column:
👉 Right-click the date-time column in the Studio page.
👉 Select the Create Buckets option from the context menu.
👉 Select the Minute of the hour option from the Select bucketing method dropdown in the Transform panel.
👉 Enter a name for your new column in the New column name field.
👉 Choose one of the options in the Create buckets using section and fill in the required fields (see detailed descriptions below):
• Custom range
• Specific values
👉 A preview of the new column will be shown in the data grid.
👉 Click Apply.

🔷 Custom range

You can use the Custom Range option to input the conditions to determine bucket labels.

👉 To do this, enter conditions using these comparative operators.
• Equal to (=), more than (>), or more than or equal to (>=) as part of the Start condition
• Less than (=3, and

08/02/2023

❇️ ❇️ Create buckets – Date (ZOHO Data Preparation) Part-3

You can classify a group of date values or individual dates using the bucketing technique.

The bucketing options for a date column are:
• Weekday or not
• Month of the year
• Week of the year
• Week of the month
• Day of the year
• Day of the month
• Minute of the hour
• Time of day
• Custom date range

🔷Week of the month

This option lets you create a new column next to the date column to classify the weeks in a month.

To apply the Week of the Month option to a date column:
👉 Right-click the date column in the Studio page.
👉 Select the Create Buckets option from the context menu.
👉 In the Operations panel, select the Week of the month option from the Select bucket options dropdown.
👉 Enter a name for your new column in the New column name field.
👉 Choose one of the options in the Create buckets using section and fill in the required fields (see detailed descriptions below):
• Custom range
• Specific values
👉 A preview of the new column will be shown in the data grid.
👉 Click Apply .

🔷Custom range

You can use the Custom Range option to enter the conditions to determine bucket labels.
👉 To do this, enter conditions using these comparative operators:
• Equal to (=), more than (>), or more than or equal to (>=), as part of the Start condition
• Less than (

08/02/2023

❇️ ❇️ Create buckets – Date (ZOHO Data Preparation) Part-4

You can classify a group of date values or individual dates using the bucketing technique.

The bucketing options for a date column are:
• Weekday or not
• Month of the year
• Week of the year
• Week of the month
• Day of the year
• Day of the month
• Minute of the hour
• Time of day
• Custom date range

🔷Day of the year

This option lets you create a new column next to the date column to classify the days in a year.

To apply the Day of the year option to a date column:
👉 Right-click the date column in the Studio page.
👉 Select the Create Buckets option from the context menu.
👉 Select Day of the year from the Select bucket options dropdown in the Transform panel.
👉 Enter a name for your new column in the New column name field.
👉 Choose one of the options in the Create buckets using section and fill in the required fields (see detailed descriptions below):
• Custom range
• Specific values
👉 A preview of the new column will be shown in the data grid.
👉 Click Apply .

🔷Custom range

You can use the Custom Range option to input the conditions to determine bucket labels.
👉 To do this, enter conditions using these comparative operators:
• Equal to (=), more than (>), or more than or equal to (>=), as part of the Start condition
• Less than (

07/02/2023

❇️ ❇️ Create buckets – Date (ZOHO Data Preparation) Part-1

You can classify a group of date values or individual dates using the bucketing technique.

The bucketing options for a date column are:
• Weekday or not
• Month of the year
• Week of the year
• Week of the month
• Day of the year
• Day of the month
• Minute of the hour
• Time of day
• Custom date range

🔷Weekday or not

This option lets you create a new column next to the date column to classify weekdays and weekends.

To apply the Weekday or Not option to a date column:
👉 Right-click the date column in the Studio page.
👉 Select Create Buckets from the context menu.
👉 Select the Weekday or not option from the Select bucket options dropdown in the Transform panel.
👉 You can set the days of the week under the sections Weekdays or Weekends.
👉 Enter a name for your new column in the New column name field.
👉 A preview of the new column will be shown in the data grid.
👉 Click Apply .


🔷Month of the year

This option lets you create a new column next to the date column to classify the months of a year. To apply the Month of the year option to a date column:
👉 Right-click the date column in the Studio page.
👉 Select the Create Buckets option from the context menu.
👉 In the Transform panel, select the Month of the year option from the Select bucket options dropdown.
👉 Enter a name for your new column in New column name.
👉 Choose one of the options from the Create Buckets Using section and fill in the required fields (see detailed descriptions below):
• Custom range
• Specific values
• 👉
A preview of the new column will be shown in the data grid.
👉 Click Apply .

🔷Custom range

You can use a custom range to input the conditions to determine the bucket labels.
👉 To do this, enter conditions using these comparative operators:
• Equal to (=), more than (>), or more than or equal to (>=), as part of the Start condition .
• Less than (

07/02/2023

❇️ ❇️ Create buckets – Date (ZOHO Data Preparation) Part-2

You can classify a group of date values or individual dates using the bucketing technique.

The bucketing options for a date column are:
• Weekday or not
• Month of the year
• Week of the year
• Week of the month
• Day of the year
• Day of the month
• Minute of the hour
• Time of day
• Custom date range

🔷Week of the year

This option lets you create a new column next to the date column to classify weeks of the year.

To apply the Week of the year option to a date column:

👉 Right-click on the date column in the Studio page.
👉 Select the Create Buckets option from the context menu.
👉 Select the Week Count option from the Select bucket options dropdown in the Transform panel.
👉 Enter a name for your new column in New Column name .
👉 Choose one of the options in the Create Buckets Using section and fill in the required fields (see detailed descriptions below):
• Custom range
• Specific values
👉 A preview of the new column will be shown in the data grid.
👉 Click Apply .

🔷Custom range

You can use the Custom Range option to input the conditions to determine bucket labels.
👉 To do this, provide conditions using these comparative operators:
• Equal to (=), more than (>), or more than or equal to (>=), as part of the Start condition.
• Less than (

06/02/2023

❇️ ❇️ Import data from Amazon S3 in ZOHO ❇️ ❇️

Zoho DataPrep supports importing data from Amazon S3 cloud storage service. Amazon Simple Storage Service, also known as Amazon S3 from AWS provides object storage through a web service interface.

🔖 🔖To import data from Amazon S3

1. Click the Cloud storage icon in the Choose a data source box.
2. Select the Amazon S3 option in the Choose a cloud storage service section.
3. Provide the details in the Connection name, Access key, and Secret key fields.

Note: If you have created a connection already, you can view the existing connection tile. Simply click the connection tile and start importing data.

4. Click the Authenticate Amazon S3 button to authenticate your account with your credentials. You will need to authenticate S3 when you try importing data for the first time.

Note: The connection configuration will be saved for accessing data in Amazon S3 in the future. Credentials are securely encrypted and stored.

5. Choose the required bucket and select the files you want to import. Click the Import button.
6. You can also search and import files using the Advanced selection option. Enter details in the Bucket name, Folder path, File pattern, and Parse file as fields to search for a file.
7. Advanced selection helps you perform dynamic file selection based on regex. This can be used for getting incremental data from your Amazon S3 bucket. The newly added file that matches the file pattern that was modified after the previous sync will be taken from your S3 bucket.
👉Bucket name : The bucket name you want to import data from.
👉Folder path : The folder path where you want to search for files. If the files are stored in the bucket without any folder, you can leave this field empty.
👉File pattern : The pattern used to match the file names in the bucket. This supports regex type matching. You can also use the pattern, ".*" to match any file in the path specified.

Note: The file pattern match is a simple regex type match.

👉Include subfolders : You can also select the Include subfolders checkbox if you want to include subfolders while searching for a file.
👉Parse file as : Choose the required extension to parse the file. If your file format is not a commonly used one, you can use this option to parse the file into one of the following formats before importing the data into a readable format. The available formats are CSV, TSV, JSON, XML, and TXT.
8. If the file is an HTML, XLS, or XLSX file, you can click the Preview option to view the sample dataset or enter the password if the file is password-protected and click Import .
9. Once you have completed importing data, you can choose to schedule this import, or you can start preparing your data right away.

06/02/2023

❇️ ❇️ Import data from Google BigQuery [Public Beta] ❇️ ❇️

Zoho DataPrep supports importing data from Google BigQuery. BigQuery is a fully managed enterprise data warehouse that helps you manage organization data.

To import data from Google BigQuery
1. Click Google BigQuery in the Choose a data source box.
2. Select an account from the saved data connections, or add a new account using the Add new option.
3. To add a new connection, enter the Project ID and click the Sign in with Google button.

Note: Project ID can be found on your Google cloud console. Google BigQuery authorizes access to resources based on verified identity.

4. After signing in with your google account, you can click Continue to allow Zoho DataPrep to access data from your Google BigQuery project for the first time.

Note: The connection configuration is securely saved for importing data from the Google BigQuery project in the future.

5. Select the tables that need to be imported. Click Import .
6. You can also use SQL query to select and import data.
7. Click Import to begin importing data from your Google BigQuery project.
8. Once you have completed importing data, you can choose to schedule this import or start preparing your data right away.