Bucket Field - gettectonic.com
Data Integration with AWS Glue
04Sep

Data Integration with AWS Glue

The rapid rise of Software as a Service (SaaS) solutions has led to data silos across different platforms, making it challenging to consolidate insights. Effective data analytics depends on the ability to seamlessly integrate data from various systems by identifying, gathering, cleansing, and combining it into a unified format. AWS Glue, a serverless data integration service, simplifies this process with scalable, efficient, and cost-effective solutions for unifying data from multiple sources. By using AWS Glue, organizations can streamline data integration, minimize silos, and enhance agility in managing data pipelines, unlocking the full potential of their data for analytics, decision-making, and innovation. This insight explores the new Salesforce connector for AWS Glue and demonstrates how to build a modern Extract, Transform, and Load (ETL) pipeline using AWS Glue ETL scripts. Introducing the Salesforce Connector for AWS Glue To meet diverse data integration needs, AWS Glue now supports SaaS connectivity for Salesforce. This enables users to quickly preview, transfer, and query customer relationship management (CRM) data, while dynamically fetching the schema. With the Salesforce connector, users can ingest and transform CRM data and load it into any AWS Glue-supported destination, such as Amazon S3, in preferred formats like Apache Iceberg, Apache Hudi, and Delta Lake. It also supports reverse ETL use cases, enabling data to be written back to Salesforce. Key Benefits: Solution Overview For this use case, we retrieve the full load of a Salesforce account object into a data lake on Amazon S3 and capture incremental changes. The solution also enables updates to certain fields in the data lake and synchronizes them back to Salesforce. The process involves creating two ETL jobs using AWS Glue with the Salesforce connector. The first job ingests the Salesforce account object into an Apache Iceberg-format data lake on Amazon S3. The second job captures updates and pushes them back to Salesforce. Prerequisites: Creating the ETL Pipeline Step 1: Ingest Salesforce Account Object Using the AWS Glue console, create a new job to transfer the Salesforce account object into an Apache Iceberg-format transactional data lake in Amazon S3. The script checks if the account table exists, performs an upsert if it does, or creates a new table if not. Step 2: Push Changes Back to Salesforce Create a second ETL job to update Salesforce with changes made in the data lake. This job writes the updated account records from Amazon S3 back to Salesforce. Example Query sqlCopy codeSELECT id, name, type, active__c, upsellopportunity__c, lastmodifieddate FROM “glue_etl_salesforce_db”.”account”; Additional Considerations You can schedule the ETL jobs using AWS Glue job triggers or integrate them with other AWS services like AWS Lambda and Amazon EventBridge for advanced workflows. Additionally, AWS Glue supports importing deleted Salesforce records by configuring the IMPORT_DELETED_RECORDS option. Clean Up After completing the process, clean up the resources used in AWS Glue, including jobs, connections, Secrets Manager secrets, IAM roles, and the S3 bucket to avoid incurring unnecessary charges. Conclusion The AWS Glue connector for Salesforce simplifies the analytics pipeline, accelerates insights, and supports data-driven decision-making. Its serverless architecture eliminates the need for infrastructure management, offering a cost-effective and agile approach to data integration, empowering organizations to efficiently meet their analytics needs. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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September 4, 2024in Salesforce
formula fields
25May

Bucket Field in Salesforce

The Bucket Field in Salesforce feature facilitates rapid categorization of values for a field in a report without requiring the creation of a custom formula field at the object level. In reporting, a bucket represents a customized category crafted by users and serves as a tool within Salesforce for reporting and documentation purposes. What is the purpose of the Bucket Field tool? The Bucket Field tool simplifies the process of organizing data and enhances reporting capabilities. By grouping records based on specific criteria, users can delve deeper into their data, enabling them to make more informed decisions. Is it possible to bucket a formula field in Salesforce? To utilize in another report, a Bucket Field must be recreated for each additional report, or a separate formula field must be created for the object depending on the bucket. Custom Summary Formulas cannot be applied to Bucket Fields. Limitations of Bucket Fields Each Bucket Field allows a maximum of 20 buckets. Bucket Fields cannot be created against Custom Summary Formulas. Reports can incorporate a total of 5 bucket fields. Can you filter on a bucket field in Salesforce? Bucketing can be utilized to group, filter, or organize report data. When creating a bucket field, users define multiple categories (buckets) used to group values in the report. Like1 Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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May 25, 2022in Salesforce
better data better forecast
04Nov

Joined Report in Salesforce

What is a joined report in Salesforce? A joined report in Salesforce consists of up to five report blocks , which you add to the report to create multiple views of your data. For each block, you can add regular and summary fields, create standard and cross-block custom summary formulas, apply filters, and sort columns.  A joined report can contain data from multiple standard or custom report types. What is the drawback of joined reports in Salesforce? Salesforce Joined report limitations A joined report in Salesforce is a report that allows you to show data that shares a relationship with one or more objects. Joined reports are often used when objects are not in parent-child relationships, such as Accounts and Opportunities. Advantages of Using Joined Reports What report types can be converted into joined reports? Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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November 4, 2021in Salesforce, Salesforce Optimization
Summary Formulas and Row Level Formulas
22Apr

Summary Formulas and Row Level Formulas

Salesforce report formulas serve various purposes, from grouping records to performing calculations and comparing data. In the Salesforce Report Builder, you’ll encounter two distinct types of formulas: Summary Formulas and Row-Level Formulas. Although they may sound similar, they serve different functions. Summary Formulas operate across multiple records, displaying their results at the bottom of a column. Conversely, Row-Level Formulas pertain to a single record and display their results directly on the corresponding row. Let’s dip into examples of both Row-Level and Summary Formulas to understand their applications in Salesforce reports. Example 1: Total Opportunity Amount Suppose your boss requests a report showing the total Opportunity Amount broken down by Country. In this scenario, you wouldn’t require a Summary Formula field. Instead, simply select the Opportunity Amount field and check the SUM checkbox. If you include a grouping based on Country, the report will automatically generate a summary line. Example 2: Average Monthly Case Volume for a Specific Product Now, imagine the support team asks for a report indicating the monthly average of Cases for a specific Product over the past year. Here, you’d utilize a Summary Formula. Ensure the Product field is set as a ‘Group By Row’ field, then select Summary Formula from the Columns drop-down. Create the formula by dividing the Record Count by 12 (the number of months in a year), and assign a column name, such as “Monthly Avg Cases.” Example 3: Checking Field Value Matches For another scenario, let’s say you’re tasked with verifying that at the Case level, the Billing State matches the Shipping State of the associated Account. With Row-Level formulas, you can accomplish this without creating a new field. Add a Row-Level Formula from the Columns drop-down, then create an IF statement comparing the Billing State to the Shipping State, resulting in either 0 (not matching) or 1 (matching). It’s valuable to note some considerations regarding Row-Level formulas, such as the limitation of one Row-Level formula per report and a maximum of five referenced fields. Additionally, Row-Level formulas cannot be used for cross-filters or buckets. Refer to Salesforce documentation for more details on restrictions. In conclusion, understanding the distinction between Row-Level and Summary Formulas empowers you to leverage the appropriate formula type effectively in Salesforce reports, optimizing your data analysis and decision-making processes. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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April 22, 2020in Salesforce, Salesforce Development Services, Salesforce Optimization

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