Get started with Snowflake Connector for MySQL

Introduction The Snowflake Connector for MySQL consists of a Snowflake Native App, installed from the Snowflake marketplace, and an Agent application running either on-premises or in the cloud. The connector facilitates data transfer from a MySQL s ...

Integrating Google Dataproc with Snowflake: A Step-by-Step Guide

Introduction Google Dataproc is a fully managed cloud service on Google Cloud Platform (GCP) that simplifies big data processing. It utilizes popular open-source frameworks like Apache Spark and Hadoop, allowing users to process and analyze large dat ...

Using Matillion variables for dynamic data integration with practical use cases

Although many articles and excellent formal documentation are available on the subject of variables in Matillion ETL, my main focus here is to make this blog serve as a more practical presentation of our experience in implementing some specific use c ...

Detecting Anomalies with Snowflake Cortex ML-based Functions

Using anomaly detection to identify outliers and alert when time series data deviates from the usual trends In my previous post about Forecasting with Snowflake Cortex ML-based Functions, I explored how to use the forecasting functionality in SQ ...

Forecasting with Snowflake Cortex ML-based Functions

Predicting sales demand based on retail sites search terms According to the Snowflake documentation, Cortex ML-based functions use machine learning to detect patterns in your data. You don’t have to be a machine learning developer to take adva ...

Demand Forecasting with Python and Snowflake

Demand forecasting Demand forecasting is a critical business process which specifically focuses on predicting the quantity of goods or services that customers are likely to purchase within a specific time frame. In order to make an accurate forecast, ...

Unlocking Efficient Data Loading: PostgreSQL to Snowflake with Change Data Capture

PostgreSQL and Change Data Capture The Change Data Capture method, also known as event sourcing, is a data loading method that extracts record-level change events (inserts, updates, deletes). In a PostgreSQL database, this method can be implemented u ...

Elixirr partners with In516ht, an Elite Snowflake Partner, to expand its EMEA technical delivery support

The partnership will bolster Elixirr’s Snowflake migration services, acting as a key competitive differentiator In516ht is delighted to announce that it is partnering with Elixirr International plc (AIM:ELIX) (“Elixirr”), the global challenger ...

IN516HT Named Matillion Rising Star Partner of the Year

IN516HT has been named Matillion’s ROW SI Rising Star Partner of the Year thanks to its team’s extensive technical skill. The Matillion Emerald Partner Network Awards recognise the innovative companies driving the data industry forward, naming an ...

Leveraging Change Data Capture Features when Loading Data from Relational Databases

Change Data Capture in the Analytical Architecture Change Data Capture (CDC) features are usually used for database replication purposes or real-time data loads. We leveraged this feature to reduce the load time from source databases to the central d ...

Maintaining a Mapping Table in Snowflake Native App

Leverage the Snowflake Native Application Framework to build an application that allows users to maintain a mapping table A Snowflake Native Application is first and foremost an application that provides some functionality. Because it is hosted on th ...

Create missing records with Snowflake SQL

Using the GENERATOR and LAST_VALUE functions This question comes up time and time again: How do I create missing records with SQL? For example, you may require exchange rates for each day within a time period, but some days are missing. Thi ...