Securely integrate Vertica Analytics Platform with Listrak
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.
With over a decade of experience, Listrak is a cloud-based digital marketing platform that focuses on providing leading retailers with specialized marketing tools to boost one-on-one customer interactions, improve business revenue, maximize customer engagement, and increase growth. By combining the power of advanced artificial intelligence, machine learning, predictive analytics, and real human intelligence, Listrak automates marketing tasks, offers powerful CRM solutions, and analyzes data from multiple platforms to drive your retail, operations, and marketing goals — all while building better relationships with your customers across all devices and channels.
Popular Use Cases
Bring all your Listrak data to Amazon Redshift
Load your Listrak data to Google BigQuery
ETL all your Listrak data to Snowflake
Move your Listrak data to MySQL
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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.
Listrak's End Points
Listrak Cross-Channel Orchestration
Listrak Cross-Channel Orchestration tools empower you to build seamless customer experiences. The platform's intuitive tools facilitate the creation of multi-stage, personalized marketing journeys that engage customers based on real-time behaviors. Listrak also gives you the ability to connect with guests one-on-one, in real-time with intelligently-triggered communication across multiple channels like SMS, email, and social media. Plus, the platform's drag-and-drop interface helps users create beautiful, responsive emails for marketing campaigns.
Listrak Customer Insights
Listrak's Customer Insights tools unlock the secrets buried in your customer data with powerful analytics and visualization features that include more than 70 pre-built visualizations for building dashboards to your specifications. Customer Insights provide a bird's eye view of each Customer Journey and seamlessly integrate with the Listrak platform to turn insights into marketing campaigns with a single click. This fuels more engaging and effective customer interactions, and informs your segmentation and automation efforts.
Listrak Behavioral-Based Triggers
Listrak monitors customer behaviors to trigger individually-tailored interactions. By tracking browsing behavior, engagement statistics, purchase information, and lifecycle incidents for customers, Listrak knows where each customer is at in their 'journey.' This allows the platform to respond to a customer's intent with specialized communications — like abandonment messages to re-engage active shoppers.
Listrak Predictive Personalization
Listrak's predictive personalization tools use machine learning, artificial intelligence, and data modeling to boost the success of marketing campaigns. By analyzing past behavioral data, these predictive analytics tools can predict the likelihood of future behavior based on different variables.
Listrak Unified 360-Degree Customer Profile
Listrak pulls data from various sources, synthesizes it, and analyzes it as a whole to identify key customer signals, and incorporate them into a 360-degree customer profile for the most accurate and actionable customer data possible.