Learn about combining data from different data sources.
- Data Analysis
- Data Integration
- Data Pipeline
- Data Warehouse
- How to Guides
What is Data Sprawl?
Data sprawl refers to the overwhelming amount and variety of data produced by enterprises every day. With the growing number of operating systems, data warehouses, various BYOD devices, and enterprise and mobile applications, it’s no wonder that the proliferation of data is becoming a problem.Read blog post
Worried about IoT? Think About Your Data Integration Plan
Trusting your IoT strategy to a cloud-based data integration solution like Alooma gives you a simple and secure method of collecting and combining all data from all sources into one location that can scale as your business needs change.Read blog post
Data Integration vs. Data Pipeline — What's the Difference?
If you're not currently in the middle of a data integration project, or even if just you want to know more about combining data from disparate sources — the first step is understanding the difference between a data pipeline and data integration.Read blog post
The Importance of Data Integration to Today’s Business
Consolidating data to a central repository enables teams across the organization to improve performance measurement, gain deeper insights and actionable intelligence, and make more informed decisions to support organizational objectives.Read blog post
MySQL to Google BigQuery Replication
A major reason to replicate your MySQL data into Google BigQuery, is the ability to join multiple data sources for valuable analysis. However, there are three approaches each with their advantages and disadvantages. Here, we’ll focus on our preferred method - Binlog Replication and show you the steps to do it.Read blog post
The easiest way to load a CSV into Google BigQuery
BigQuery, Google’s data warehouse as a service, is growing in popularity as an alternative to Amazon Redshift. If you’re considering working with BigQuery, you’ll find that accessing the data is quite straightforward.Read blog post
Six pitfalls when connecting Elasticsearch to Redshift
Redshift and Elasticsearch have a very different structure, as they are two very different solutions for data storage. While Elasticsearch is a full-text search engine based around schema-free JSON documents, Redshift is an SQL-based, columnar, schema’d data warehouse based on PostgreSQL.Read blog post
Use webhooks to integrate data sources with Alooma
Use webhooks to integrate any SaaS product to your data warehouseRead blog post
Export Application Insights to Amazon Redshift with Alooma
Learn how to export Application Insights data to Amazon Redshift with AloomaRead blog post