Connect Vertica Analytics Platform to CallRail

These companies automate their data pipelines using Integrate.io

About Vertica Analytics Platform

Extract, transform, and load data to Vertica. Ingest data from Vertica and load to other destinations.

About CallRail

CallRail provides businesses with tracking phone numbers that they can use to gather valuable customer interaction data from phone calls. This includes the source of the call - an advertisement on social media, for example - as well as information about the callers themselves. Additionally, once a call is completed, CallRail automatically generates a transcript of the call. By gathering this data, CallRail allows businesses to score their leads more easily and gauge the effectiveness of different marketing campaigns.

Popular Use Cases

Bring all your CallRail data to Amazon Redshift

Load your CallRail data to Google BigQuery

ETL all your CallRail data to Snowflake

Move your CallRail data to MySQL

Vertica Analytics Platform's End Points

Vertica Massively Parallel Processing (MPP)

Through its MPP architecture, Vertica distributes requests across different nodes. This brings the benefit of virtually unlimited linear scalability.

Vertica Column-Oriented Storage

Veritica's column-oriented storage architecture provides faster query performance when managing access to sequential records. This advantage also has the adverse effect of slowing down normal transactional queries like updates, deletes, and single record retrieval.

Vertica Workload Management Automation

With its workload management features, Vertica allows you to automate server recovery, data replication, storage optimization, and query performance tuning.

Vertica Machine Learning Capabilities

Vertica includes a number of machine learning features in-database. These include 'categorization, fitting, and prediction,' which bypasses down-sampling and data movement for faster processing speed. There are also algorithms for logistic regression, linear regression, Naive Bayes classification, k-means clustering, vector machine regression/classification, random forest decision trees, and more.

Vertica In-Built Analytics Features

Through its SQL-based interface, Vertica provides developers with a number of in-built data analytics features such as event-based windowing/sessionization, time-series gap filling, event series joins, pattern matching, geospatial analysis, and statistical computation.

Vertica SQL-Based Interface

Vertica's SQL based interface makes the platform easy to use for the widest range of developers.

Vertica Shared-Nothing Architecture

Vertica's shared-nothing architecture is a strategy that lowers system contention among shared resources. This offers the benefit of slowly lowering system performance when there is a hardware failure.

Vertica High Compression Features

Vertica batches updates to the main store. It also saves columns of homogenous data types in the same place. This helps Vertica achieve high compression for greater processing speeds.

Vertica Kafka and Spark Integrations

Vertica features native integrations for a variety of large-volume data tools. For example, Vertica includes a native integration for Apache Spark, which is a general-purpose distributed data processing engine. It also includes an integration for Apache Kafka, which is a messaging system for large-volume stream processing, metrics collection/monitoring, website activity tracking, log aggregation, data ingestion, and real-time analytics.

Vertica Cloud Platform Compatibility

Vertica runs on a variety of cloud-based platforms including Google Cloud Platform, Microsoft Azure, Amazon Elastic Compute Cloud, and on-premises. It can also run natively using Hadoop Nodes.

Vertica Programming Interface Compatibility

Vertica is compatible with the most popular programming interfaces such as OLEDB, ADO.NET, ODBC, and JDBC.

Vertica Third-Party Tool Compatibility

A large number of data visualization, business intelligence, and ETL (extract, transform, load) tools offer integrations for Vertica Analytics Platform. For example, Integrate.io's ETL-as-a-service tool offers a native integration to connect with Vertica.

CallRail's End Points

CallRail Companies

Create separate companies with different configurations and tracking numbers. Then, you can retrieve information like the company’s name, creation date, lead scoring settings and company ID. This will allow you to track each different parameter in your analytics.

CallRail Users

Track any users who have access to your call data at various permission levels. This field provides you with contact information about the user - including their name, email, user ID, role and company - so that you can integrate your user and company data for analysis.

CallRail Accounts

Retrieve an account’s name and ID and choose whether or not to enable outbound call recording. Since this is the top level object for CallRail, you can also use that account ID to integrate data - such as “Company” or “Tracker” - that is generated by any lower level object within that account.

CallRail Integrations

Retrieve data from other data sources by integrating CallRail data with third party tools. The data in this field includes the name of the third party tool being integrated, the type of integration, its status, the unique integration ID, and associated companies. CallRail can use all of this data to provide more robust marketing analytics.

CallRail Trackers

Gather call data from tracking numbers that can either be linked to a specific source or associated with a particular visitor. This field can retrieve a variety of data from those calls, including the tracker ID, tracking numbers and associated companies. This information can help you qualify leads and gauge the effectiveness of marketing campaigns.

CallRail Calls

Retrieve data on an individual call, including the duration, source, phone number and status i.e., whether it was answered, missed, etc. Additionally, you can retrieve contact information for the caller, including their name, phone number, and whether or not CallRail rates the call as having provided a good lead.

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Integrates With

Microsoft Azure SQL Database

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8x8

AS400

AdRoll

Aftership

Airtable

AlloyDB

Amazon Aurora

Amazon Kinesis

Amazon RDS

Amazon Redshift

Amazon S3

Amplitude

AppsFlyer

Asana