Securely integrate Vertica Analytics Platform with Xero
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.
Xero is an online accounting software that allows small businesses to take complete control over their cash flow and their finances. Use Xero’s time-saving tools to process invoices, manage your bills and expenses, reconcile transactions, and run your business on the go.
Popular Use Cases
Bring all your Xero data to Amazon Redshift
Load your Xero data to Google BigQuery
ETL all your Xero data to Snowflake
Move your Xero 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.
Xero's End Points
Retrieve, add, update, or attach files to contacts in a Xero organization. Then, enrich and integrate this data to get accurate insights and send targeted communication.
Take full control of your financial accounts: attach files, archive accounts, update details, delete accounts, and more. Use this information to get a well-rounded understanding of your financial standing and make any necessary strategic improvements.
Add, update, retrieve or delete both tracked and untracked items in your inventory. This will give you a better idea of what’s selling, what’s not, and where you should take your business.
Create, update, delete, void, and retrieve sales invoices or purchase bills. Monitor this data and use it to gain a clearer view of your expected revenue gains and losses. This, in turn, will help you to run accurate predictive analyses.
Retrieve, delete, add, or update draft expense claim receipts. Monitor this information to take full control over your transactional information.
Refund credit notes, reverse a payment, apply payments to approved AR and AP invoices, and refund prepayments and overpayments. Then, use your payment data to track how much you are making from specific customers or during specific time periods. This will allow you to hone your marketing efforts and score leads more effectively.
Review your most commonly viewed reports in Xero, and use data to improve your efficiency and gain actionable insight.