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.
Facebook Ads generates valuable data that can help you better focus your marketing pursuits both on Facebook and in other advertising ventures. It provides you with tools to track your ad performance at all levels, from a single ad to a whole ad campaign and provides insights that can show you exactly how those ads are converting into actual sales.
Bring all your Facebook Ads data to Amazon Redshift
Load your Facebook Ads data to Google BigQuery
ETL all your Facebook Ads data to Snowflake
Move your Facebook Ads data to MySQL
Through its MPP architecture, Vertica distributes requests across different nodes. This brings the benefit of virtually unlimited linear scalability.
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.
With its workload management features, Vertica allows you to automate server recovery, data replication, storage optimization, and query performance tuning.
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.
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's SQL based interface makes the platform easy to use for the widest range of developers.
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 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 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 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 is compatible with the most popular programming interfaces such as OLEDB, ADO.NET, ODBC, and JDBC.
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.
Track data on your ad campaigns, including the Facebook campaign objective, duration, and status - as well as campaign and account ID's that will allow you to easily integrate this data with related data from other sources.
View information about an individual ad, including what ad set it belongs to, the image used in an ad, and how much you are bidding for the ad's use. Then, use that data to track the overall advertising cost of this ad along with its individual performance within an ad set.
Monitor the performance of a collection of Facebook ads that share a single criteria and budget. This data includes the budgeted amount, what remains from your Facebook Ads budget, and how that ad set is targeted.
See the ways in which your Facebook ads are turning into revenue for your business by tracking cost-per-click, number of conversions, and the type of conversions you are getting. Then you can integrate that data with your ad sets, campaigns, and accounts via their unique ID's.