Integrate Vertica Analytics Platform with Delighted
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.
Delighted is a service that employs single question surveys to provide businesses with real-time customer feedback. Each survey question can have a rating scale for customers to select from as well as a section where customers have the option to leave a free-form comment. This provides both a numerical score - that can be collected to create a Net Promoter Score (NPS) - and useful customer feedback that Delighted can filter and search to retrieve the most useful responses for a given purpose.
Popular Use Cases
Bring all your Delighted data to Amazon Redshift
Load your Delighted data to Google BigQuery
ETL all your Delighted data to Snowflake
Move your Delighted 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.
Delighted's End Points
Create a survey recipient, including their customer ID, email address and phone number. Then, you can customize your survey delays based on your customers’ needs and preferences, specifying how you want the surveys sent - via SMS or email - and how frequently you want them sent.
Delighted Survey Responses
Retrieve data from customer responses, including the score they selected, any comments they left in response to the survey and the person ID for the customer (which allows you to continue to track their responses). Additionally, use this data to create and update your Net Promoter Score, which can help provide customer analytics both within Delighted and in other data sources via integration.
View important metrics for your account like your NPS and the percentage of your respondents that identified as promoters, passives, or detractors. This provides a broader view of your survey performance that can help you determine your overall business performance.
When someone unsubscribes, you can maintain their previous survey response data and view their old emails. When integrated with other user data, this information can provide key business insights. It can also be used to run an array of business analyses, including predictive analytics.