Ask an Architect: 5 Steps to an Effective Salesforce Data Management Strategy (Part 2)

“We have millions of records and constituents with high expectations around service and engagement; how do we develop an effective data management strategy?”

In Part 2 of this blog post, we continue the discussion of effective CRM data management as an integral part of delivering a remarkable constituent experience across all channels, particularly for organizations with large data volumes. And the Salesforce platform offers a number of features that make it easy to develop a common sense approach to data management that can deliver happier constituents, a more effective user experience, improved organizational agility, and reduced maintenance and cost.

An effective CRM data management strategy is founded on a solid understanding of your business process, user behavior and technology, and succeeds when you combine it with governance and disciplined execution.

Watch Webinar

Consider these 5 steps when building your Salesforce Data Management Strategy:

1. 1. Take Only What You Need: CRM-Relevant Data

 

1. 2. Optimize your Big Objects: Large Data Volume Optimization

 

1. 3. Use Data Where it Lives: Federate and Integrate Non-CRM Data

 

1. 4. Travel Light: Data Archiving

 

5. Govern with Discipline: Master Data Management

In Part 1 of this blog, we explored Steps 1 and 2. In this second part of the blog, we’ll explore the remaining steps.

3. Use Data Where it Lives: Federate and Integrate Non-CRM Data

Federation and integration options enable data access from external sources, embedding of external web apps, and syncing of data with Salesforce.

The following is a table of various Salesforce solutions to align your data.

Result: Enriches end user view and capabilities, and may reduce cost.

Technology Options	What Is It?	When To Use It?
Salesforce Connect	Configuration based, uses oData services for Read/Write access to external data through Salesforce external objects	Display/modify constituent’s transactions/asset records stored in another system via oData services or a custom connector Supports mobile/Salesforce1
Heroku Connect / Heroku External objects	Syncs up data from Heroku Postgres database to Salesforce Objects. Can also expose Heroku data as Salesforce external objects	Access data from a Heroku app (such as Event Management, public facing mobile app etc.) and display / sync it with Salesforce Supports mobile/Salesforce1
Web Services/Mash-Up	Custom visualforce / apex code or lightning component to access data via web services, or UI mashups via Canvas and iFrame etc.	Enable access to other systems such as degree planning, online coursework, registration/SIS from a portal style UI Supports mobile/Salesforce1*
Einstein Analytics (Wave)	Embed structured and unstructured (chats/tweets) data insight, analytics and exploration capability for large data sets	Access to Salesforce and non-Salesforce data that runs into Millions of records such as system generated (IoT, Sensor data, Web Analytics) Supports mobile/Salesforce1*

Here is some additional information on integration and federation options.

Technology Options	Level of Effort/Complexity	Examples
Salesforce Connect	Complexity: Medium – High Effort: High (Weeks – Months) Creating oData-compliant services can take time. If they exist, or can be easily created via Middleware, the rest is configuration based.	View shipment status of promotional item sent as thank you gift on a Contact record in Salesforce as a related list.
Heroku Connect / Heroku External objects	Complexity: Medium – High Effort: High (Weeks – Months) Creating the Heroku app / UI can take time. It is exists, the rest is configuration based and can be relatively quick.	Sync of LMS / event attendance data from a Heroku based app.
Web Services/Mash-Up	Complexity: Medium – High Effort: High (Weeks – Months) Depends on the technical design, iFrames are quick to implement, but custom components and Canvas can take time. Authentication can also increase complexity.	View grades from SIS on a Contact record in Salesforce as a related list.
Wave Analytics	Complexity: High Effort: High (Weeks – Months) Importing data into Wave, testing and configuration may take a few weeks. Embedding Wave UI in Salesforce is relatively quick.	Website traffic, community posts, and donation comparison/correlation.
Salesforce Connect	Complexity: Medium – High Effort: High (Weeks – Months) Creating oData-compliant services can take time. If they exist, or can be easily created via Middleware, the rest is configuration based.	View shipment status of promotional item sent as thank you gift on a Contact record in Salesforce as a related list.

4. Travel Light: Data Archiving

Relevant data is the key to successful CRM. The rest is history. Determine relevance by identifying how data is driving insights and behavior.

Result: Reduces data volume, improves performance and may reduce cost.

The following is a table of various archiving tools, and information on what each of these options may take to implement.

Technology Options	What Is It?	When To Use It?
Data Extracts	Simple data extract data, usually as .csv files directly from Salesforce or with another ETL tool.	To extract historical data out of Salesforce to an external system or store as flat files.
Data Extracts via Bulk API	A Salesforce API to extract and delete large number of records in a batch mode.	Used for large sets of data, programming batch jobs to regularly extract and delete.
Big Objects	New Salesforce feature to store billions of record in a read-only format on the same trusted Salesforce platform.	Used to store billions of records from an existing object onto a Big Object for direct data access.
Heroku Based Solutions (e.g Cervello)	Partner and Open Source Solutions to archive Salesforce data on Heroku/Postgres platform	When archiving and unarchiving records into Salesforce is needed, and the archiving platform needs to be tightly integrated.
AppExchange Archiving Solutions	Chatter or Attachments Archive.	When archiving records from Salesforce to an external platform.
Others / Custom Solutions – Data Lakes, Data Warehousing etc.	Custom solutions that archive/merge CRM data along with other system data.	To access large amounts of data for historical reporting with a BI tool.

Here is some additional information on what each of these options may take to implement.

Data Extracts via Bulk API	Complexity: Medium Effort: Medium – High (Weeks-Months) Programming skills required.	Old activities and case records extracted and deleted via a daily batch process.
Big Objects	Complexity: High Effort: Medium – High (Weeks-Months) XML and Apex skills required.	Legacy information about direct mail campaigns sent and received by individuals.
Heroku Based Solutions (e.g Cervello)	Complexity: Medium – High Effort: High (Months) Analysis, configuration and testing can be lengthy.	Very old student data preserved mainly for future compliance and legal reasons.
AppExchange Archiving Solutions	Complexity: Medium-High Effort: Medium-High (Weeks-Months) Analysis, configuration and testing can be lengthy.	Archive Chatter posts and Attachments, other data that is outdated / not in use.
Others / Custom Solutions – Data Lakes, Data Warehousing etc.	Complexity: High Effort: High (Months) Typically enterprise-wide efforts, require specific skills.	Donation records, contacts / volunteers inactive over years, financial transactions that are 4-5 year old.

5. Govern with Discipline: Master Data Management

Creating formal governance procedures will direct the alignment of CRM data collection and analysis, with business requirements designed to achieve the enterprise’s goals.

Result: Define procedures for data management to build a strong, high-performing CRM

The following is a table of teams to consider creating to build a comprehensive governing strategy.

Team	Purpose
Center of Excellence	Ensure CRM changes support business goals and follow IT best practices and processes.
Release Management	Design and document a complete release management process
Design Standards	Follow key standards for coding, testing, integration, large data volumes, and other areas that affect services
Quality Control	Create regular cadence of code reviews, data quality inspections, and analysis for code improvement

This is part 2 of a 2-part blog series on data management for large data volumes. Refer to the first installment of this series. Join us for our “5 Steps to an Effective Salesforce Data Management Strategy” webinar on February 27, 2018.

Webinar on Demand

---

This blog is also part of our larger “Ask an Architect” content series. To learn more about engaging a Salesforce.org Customer Success Architect in your organization, please contact your Account Executive.