Vertica Analytics Platform
Intercom

Integrate Vertica Analytics Platform with Intercom

About Vertica Analytics Platform

Vertica Analytics Platform is a data warehouse management system optimized for large-scale, rapidly-growing datasets. By using a column-oriented architecture (instead of row-oriented), Vertica can offer high-speed query performance for your business intelligence, machine learning, and other query-intensive systems. Vertica is compatible with a variety of cloud data warehouse servers such as Google Cloud Platform, Amazon Elastic Compute Cloud, Microsoft Azure, and on-premises. The platform also offers its “Eon Mode,” which achieves optimum performance by separating computational processes from storage processes. Eon Mode is available when hosting the platform on AWS or when using Pure Storage Flashblade on-premises. Vertica is an open-source product that is free to use up to certain data limitations.

About Intercom

Intercom is a powerful set of tools for better managing your company’s customer support system. It includes a help center with a feedback system, which you can use to focus future articles on the growing needs of your customers, and it also provides a robust conversation system that allows you to assign support teams to customers based on specific criteria (about the customer or discussion topic), rather than just based on availability. Intercom is designed to create a more effective customer support network by specifically tracking and targeting your customers’ needs.

Popular Use Cases

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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, Xplenty's ETL-as-a-service tool offers a native integration to connect with Vertica.

Intercom's End Points

Intercom Conversations

Track the content of conversations and who is involved in them. This can be used to generate data about which topics customers are most concerned with so that you can further focus your support efforts accordingly.

Intercom Tags

Sort specific groups of users and companies that you are communicating with by creating an easily searchable tag that permeates all of your intercom databases, and you can use that tag to integrate other data about those groups throughout intercom.

Intercom Users

Collect valuable customer data for your CRM, including basic contact info such as name, email address, and phone number but also more specific data, such as when they signed up, last signed in, and the tags associated with them.

Intercom Companies

Track the progress of your business relationship with companies (including a list of their users). Use that data to monitor how well your support network is meeting a company’s needs and how much of your overall revenue comes from each of the companies that are interacting with your business via intercom.

Intercom Segments

Automatically categorize users based on set criteria. Then Intercom can assign support teams based on that criteria, which allows you to more easily match customers with the support team members that can best assist them.

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