Vertica Analytics Platform
Pipedrive

Integrate Vertica Analytics Platform with Pipedrive

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 Pipedrive

Pipedrive creates a visual sales pipeline that allows businesses to better manage each stage of their deals. Additionally, Pipedrive provides detailed analytics that show how many deals are won and lost, what stages they are lost at, and how individual agents are performing based on various metrics.

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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.

Pipedrive's End Points

Pipedrive Deals

Retrieve information - like deal ID, associated users, estimated timeline and expected revenue - about any deals that your company has engaged in. This will allow you to better gauge the profitability of individual deals or track deal trends throughout your sales history.

Pipedrive Persons

Add, track, or modify contacts that have begun their journey through your sales pipeline. You can see what deals are attached to a person, what organizations they belong to, and what activities are scheduled for that person. This information can help you decide the best course of action for moving that person along your sales pipeline and winning the deals you have with them.

Pipedrive Products

Track products that your company is selling - by product name, price, or product code - or associate products with specific deals in your pipeline. This will give you a more detailed view of the revenue generated by specific products, allowing you to better prioritize them in your sales pipeline.

Pipedrive Activities

Fetch data about an activity that is scheduled in your pipeline. This could include things like the activity’s type, due date, and status, along with associated deals, contacts, and organizations. Then, use that data to track the progress and effectiveness of various activities that are being performed to help you win deals.

Pipedrive Organizations

Get data about an organization that has deals in your pipeline, including the organization’s ID, associated persons, and related deals. This will allow you to track which organizations are delivering the most profitable deals and the best leads.

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