Data Accelerator

Data Accelerator is a cloud-based data management solution that is quickly onboarded to allow for analysis, insights, and visualization of your data.

The ability to get your database environment deployed and functioning within weeks so you can build insights is a huge win. You can start small with your data management, then expand as needed.

Data Accelerator helps you:

Match individuals across disconnected data sources
Comply with CCPA and GDPR regulations
Build better customer experiences and prospect audiences
Accelerate into cloud-based data management
Generate analytics and reporting
See ROI on marketing and CRM data
Power leading marketing platforms, like Salesforce Marketing Cloud and Adobe Marketing Cloud
Quickly stand-up industry-specific reporting with built in dashboard templates (abandoned cart, fundraising, and more)

Built on the cloud platform of choice

With a modular approach to solving your marketing needs today and as they evolve, our Data Accelerators are pre-configured to get your data up and running from online and offline channels on the following platforms:

Amazon Web Services (AWS)
A leader in the cloud space, with a suite of tools (S3 Storage, RedShift Database, etc.) perfect for Data Accelerator in either a Merkle-hosted or client-hosted environment.

Google Cloud Platform (GCP)
Data Accelerator integrates with Google Cloud Platform and Google Marketing Platform, leveraging our serious strength in the ad tech space. Big Query is friendly with multiple tools (Looker, Tableau, Python, R, etc.) to further enhance, analyze and visualize your data.

Easily expand Data Accelerator’s functionality with our pre-built extensions

Get more out of your Accelerator with additional tools, services, and/or integrations to further enhance your existing data.

Salesforce Interaction Studio (IS)
Salesforce Interaction Studio (IS) is a powerful customer data platform and Data Accelerator was built to tightly integrate with it, acting as a rapid data ingestion tool that identifies and dedupes disparate data.

Adobe Experience Platform (AEP)
A leading customer data platform that not only has full integration with the other Adobe Cloud products but can also harness the power of the Data Accelerator.

Privacy Accelerator
Data privacy laws require compliance and preference management. Look up and view individual customers while managing personal data privacy requests.

DataSource
With over 2,000 data attributes across sociographic, demographic, and purchase history, DataSource provides a robust foundation for the all-channel marketer seeking to influence the entire customer journey.

Nonprofit
Built with Nonprofit marketers and fundraisers in mind, our Nonprofit extension stitches together disparate data sources to quickly enable campaign and reporting uses cases that accelerate ROI. Learn more here.

Operational Scorecard
View your data loaded into the Data Accelerator solution. The dashboards provide both an aggregated view of data loading trends, job status, and a detailed view for proactive analysis.

Audience Profile and Retail Behavior Dashboards
Understand your customer and prospect profile and explore their purchase and engagement behavior using an interactive set of dashboards and self-service tools across socio-demographic, geographic, and recency, frequency, and monetary (RFM) attributes)

Audience Snapshot
Leverage the power of the Merkle ID that supplies terrestrial identities for the individual, address, and household, and helps users understand the growth and quality of your contactable universe.

Retail Accelerator
Built with retail industry marketers in mind, our Retail extension is a set of standard tables and fields built on Merkle best practices to enable standard reporting, analytics and campaign management.

Meet Our Team

Srini Krishnamurthy

SVP, Data Management, Merkle

Michael Deeter

Vice President, Database and ETL Capability Lead

Jon Regan

Vice President, Technology & Data Management

Frequently Asked Questions

What cloud platforms and query tools do the Data Accelerator offer?

Data Accelerator is available across several cloud platforms including Google Cloud Platform (GCP), Amazon Web Services (AWS) and Microsoft's Azure. The query tools that Data Accelerator offers include: Google Big Query, Amazon Redshift, Snowflake and Azure Query Editor.

What types of data can be fed into the Data Accelerator?

Data Accelerator currently handles flat file data feeds that have fields either in a fixed width format or separated by a delimiter (comma, pipe, tab). In addition, Data Accelerator can extract data from existing database (SQL, Snowflake, Big Query, RedShift, Azure Data Warehouse) tables. For Data Accelerator clients who select Google Cloud Platform (GCP), there are numerous native Google platforms that can be pushed directly into Big Query using Data Transfer Service (DTS) or Storage Transfer Service (STS).

Can Data Accelerator handle feeds that are compressed and/or encrypted?

Data Accelerator is able to decompress files that are zipped as well as decrypt files that have been PGP encrypted. We recommend that any feeds that have PII, be transferred as encrypted using Merkle's Public Key (supplied by Merkle Data Accelerator team).

I need to make a change to a data feed (e.g. I need to add a column) that has already been onboarded. What should I do?

Before sending the new feed in the new layout, please email [email protected] and provide details such as the feed name and when the change will be made. The Data Accelerator Support team will work with you on making these changes and scheduling when the new feed will be productionalized.

How should I send a new, ad hoc data feed?

If the feed contains any Pll, clients should not be sending this feed as ad hoc due to recent changes in US and EU laws. For non-Pll feeds, if you have a new set of data you want to push into Data Accelerator and it will not be a reoccurring data source, you can push this feed to Data Accelerator by uploading it to the assigned landing location.

When pushing a new feed into Data Accelerator, how does the system perform automatic schema detection?

Data Accelerator's automatic schema detection scans any unknown file it receives to evaluate each column of data and uses AI to assign the most appropriate datatype and stage the file into the database. This is not infallible and bad data in the source feed can throw it off. For Example: A column of data is called 'product_price' and 99% of the records are sent in a decimal format but 1% of the records are sent with the text "Free". Data Accelerator will assign this column a data type of 'string' and not 'float' since there was text detected.

What are some best practices when sending a file?

Files should always have a date and time stamp in the filename (YYYYMMDDHHMMSS) and should not have any spaces in the name (Good: Order_Details_20190109110203.txt Bad: Order Details.txt).

Does Data Accelerator accept SSH keys for file delivery?

Yes. SSH keys are preferred and if a client is sending data via a secure FTP without SSH, there will be a requirement to reset the sFTP password every 60 days. SSH Keys or approval from client’s Security Officer to remove the password expiration are necessary to relax this requirement.

What are some best practices for sending data inside a file?

Include a column header
Column headers should not have any spaces or special characters. All lowercase characters is highly preferred.
Do not use column names that can also be considered SQL commands (Ex: 'date', 'order', 'trim', etc.)
When sending a date field, these should be sent as YYYY-MM-DD.
If sending date / time stamp values, the following formats are accepted YYYY-MM-DD HH:MM:SS or YYYY-MM-DD HH:MM:SS.MMM
Field delimiters can be either pipe, tabs, semi-colons or commas. Be aware of your data values and if some text values have commas in them, choose a different delimiter
Record delimiters can be either Carriage Returns and/or Line Feeds
It is strongly recommended that you use text qualifiers around your data values, especially if they potentially contain a value that is also serving as the delimiter (Ex: comma, pipe, etc.)
NaN and NaT values are not also acceptable as NULL values.
A single column file MUST have a header record

How will Data Accelerator help me with Salesforce Marketing Cloud and Adobe Marketing Cloud?

Merkle’s Data Accelerator was built to be a centralized foundation to ingest and consolidate disparate data sets. The Data Accelerator can serve as a one-stop-shop for all data to flow into a client’s Activation layer (Salesforce, Adobe, etc.).