Best practices and lessons learned for modern cloud ETL to data warehouse.
Database Migration Challenges
Database migration isn’t always as straightforward or simple as it may seem. Here are the top challenges to keep in mind as your organization prepares to move its databases from one platform to another.Read blog post
Tips for a Successful Cloud Migration
In this article, you'll get tips and suggestions to make your migration to the cloud go smoothly.Read blog post
Database Migration Tools
Database migration tools are typically categorized as on-premise, open source, or cloud-based. Which type of tool you’ll need depends on a variety of factors. Learn more.Read blog post
Common Data Migration Mistakes
Migrating data can be more complex than it looks, and many of the challenges are made up of the things we forgot to do or assumed we didn’t need to do. Let’s take a look at a few of the common issues that can trip you up when migrating data.Read blog post
How to Plan a Data Migration Project
Pre-migration planning is essential to the success of any data migration project. In this article, learn about the four steps to a successful data migration.Read blog post
What is Database Migration?
Database migration — in the context of enterprise applications — means moving your data from one platform to another.Read blog post
What is Big Data Architecture?
Big data architecture is the overarching system used to ingest and process enormous amounts of data (often referred to as "big data") so that it can be analyzed for business purposes.Read blog post
What is Data Preparation?
Data preparation is a process of gathering, cleansing, and organizing data so that it can be analyzed. Learn more.Read blog post
Alooma signs an agreement to join the Google Cloud family
We are thrilled to share that Alooma has entered into an agreement to join Google Cloud.Read blog post
The Top Cloud Data Security Challenges
As cloud computing grows in popularity and transforms how companies collect, use, and share data, it also becomes a more attractive target for would-be attackers and hackers. Learn about the top cloud data security challenges IT pros should pay special attention to.Read blog post
What is Data Integrity?
Data integrity is the assurance of accuracy and consistency of data over the course of the data life cycle (from when the data is recorded until it is destroyed).Read blog post
What is Business Intelligence?
Business intelligence (or BI) is a process used by companies to analyze their data and create actionable takeaways that impact the company’s performance.Read blog post
What is Data Mining?
Data mining is the automated process of sorting through huge data sets to identify trends and patterns and establish relationships.Read blog post
What is Data Mapping?
Data mapping is a necessary component of the larger processes of data migration and data integration. It’s a mechanism that matches fields from data sources (system A) to the target fields in a data warehouse or other storage repository (system B).Read blog post
What is Data Validation?
Data validation is a method for checking the accuracy and quality of your data, typically performed prior to importing and processing.Read blog post
Data Lake vs Data Warehouse
Data lakes and data warehouses are critical technologies for business analysis, but the differences between the two can be confusing. This article seeks to demystify these two systems for handling your data.Read blog post
What is Data Profiling?
Data profiling is a process of examining data from an existing source and summarizing information about that data. You profile data to determine the accuracy, completeness, and validity of your data.Read blog post
What is Data Loading?
Data loading refers to the "load" component of ETL. After data is retrieved and combined from multiple sources (extracted), cleaned and formatted (transformed), it is then loaded into a storage system, such as a cloud data warehouse.Read blog post
Creating a Data Strategy
This article will guide you through the kinds of questions you'll need to explore as you're planning your data strategy and starting to think about your data architecture.Read blog post
What is Data Consolidation?
Data consolidation is the process of combining all of your data wherever it may live, removing any redundancies, and cleaning up any errors before it gets stored in one location, like a data warehouse or data lake.Read blog post
Now That IoT Is Everywhere, What Do You Do About It?
Learn about what gets in the way of effectively mobilizing your data and what you can do about it to embrace IoT with greater confidence.Read blog post
What are Data Silos?
A data silo is a collection of information in an organization that is isolated from and not accessible by other parts of the organization. Removing data silos can help you get the right information at the right time so you can make good decisions.Read blog post
A Guide to Cloud Migration
Companies today have access to more data than ever before. And that data is growing at a breakneck pace. Getting all that information, from all those sources, together into a cloud repository is crucial to business, whether it's traditional analytics or cutting-edge machine learning and artificial intelligence.Read blog post
What is Data Redundancy?
Data redundancy occurs when the same piece of data is stored in two or more separate places. In this article you'll learn all about data redundancy, including how it occurs, why it's a problem, and how a modern data pipeline can reduce it.Read blog post
The State of ETL: Traditional to Cloud
Though the ETL process and traditional ETL tools have been serving the data warehouse needs, the changing nature of data and its rapidly growing volume have stressed the need to move to a modern, cloud-based solution. Learn more.Read blog post
Data Pipelines of Tomorrow
In this article, we'll look at a few aspects of data — and data pipelines — of the future: directionality, compatibility with emerging technologies, and regulatory compliance with the immutable, ordered event log. We'll also look at scalability, performance, and design(ability).Read blog post
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
What is Data Transformation?
Data transformation is the process of converting data from one format or structure into another format or structure.Read blog post
Top Data Science Tools
Learn about the best data science tools available to help you collect, store, analyze, and visualize your data, as well as incorporate the power and possibilities of machine learning.Read blog post
What is Data Extraction?
Data extraction is a process that involves retrieval of data from various sources. Frequently, companies extract data in order to process it further, migrate the data to a data repository (such as a data warehouse or a data lake) or to further analyze it.Read blog post
Fueling the Modern Data Science Stack
Learn how Alooma bridges the distance between where your data currently sits to its potential in ML contained within S3, allowing you to gain access to your own data so that you can utilize ML and AI more effectively.Read blog post
Data Warehouse Solutions: On-Prem and Cloud-Based
Learn about different on-prem and cloud-based data warehouse solutions and the factors you should use to evaluate such as features, functionality, and use cases.Read blog post
Data Mapping Tools
Learn about the various types of data mapping tools, including on-premise, open source, and cloud-based.Read blog post
Cloud Data Migration Tools
There are three primary types of tools to consider when migrating your data to the cloud: on-premise, open source, and cloud-based. Learn more.Read blog post
NoSQL vs SQL Databases: Differences Explained
Learn the key differences between SQL and NoSQL - or, relational databases and non-relational databases, and which database type you should choose.Read blog post
What is ETL?
ETL stands for "Extract, Transform, Load", and is the common paradigm by which data from multiple systems is combined to a single database, data store, or warehouse for legacy storage or analytics.Read blog post
What is Data Streaming?
Data streaming is the process of sending data records continuously rather than in batches. Generally, data streaming is useful for the types of data sources that send data in small sizes (often in kilobytes) in a continuous flow as the data is generated. Learn more.Read blog post
What is Data Quality?
Whether you’re launching a new product or service, or simply responding to the moves of your biggest competitor, making smart, timely business decisions depends almost entirely on the quality of data you have at hand.Read blog post
What is ELT?
ELT stands for Extract, Load, Transform. ELT is an evolution of the traditional system where you would extract, transform and then load the data. Learn about the benefits and drawbacks of ELT, and what a modern solution looks like.Read blog post
A Modern Approach to Data Migration
When it comes to Data Migration, we shouldn't settle for "good enough". Today's goal should be to spend less time in the ETL part of the process so that you have better data, more data, available sooner.Read blog post
How to Load Oracle Data Into BigQuery
Getting data from your Oracle database into your BigQuery data warehouse is the first step in setting up a powerful analytical workflow and getting valuable insights from your data. Learn how Alooma makes the whole process simple and affordable.Read blog post
Data Migration Tools
There are three primary types of data migration tools to consider when migrating your data: On-premise, open source, and cloud-based. Learn more.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
ETL Process: Traditional vs. Modern
ETL is a process that involves extracting data from disparate sources, transforming it, and loading into a target data store, typically a data warehouse. Learn more about the extract, transform, and load process here.Read blog post
Database Replication: Getting Your Data from There to Here
Learn about each of the three common methods of data replication and how to choose an option that works best for you.Read blog post
How to Load MongoDB Data Into Snowflake
Getting your MongoDB data into your Snowflake data warehouse is the first step in setting up a powerful analytical workflow and getting valuable insights from your data. Follow this tutorial to learn how to easily load your MongoDB data into Snowflake.Read blog post
What is Data Migration?
Data migration is simply the process of moving data from a source system to a target system. The concept of data migration is simple, but it can sometimes be a complex process. Learn more.Read blog post
How to Load MongoDB Data Into Redshift
Getting your MongoDB data into your Redshift data warehouse is the first step in setting up a powerful analytical workflow and getting valuable insights from your data. Follow this tutorial to learn how to easily load your MongoDB data into Redshift.Read blog post
ETL vs ELT: Differences Explained
The difference between ETL and ELT has to do with the order in which these processes take place. Each of these methods is well-suited to different situations. Learn more.Read blog post
How to Load Salesforce Data Into BigQuery
Getting your Salesforce data into your BigQuery data warehouse is the first step in setting up a powerful analytical workflow and getting valuable insights from your data. Follow this tutorial to learn how to easily load your Salesforce data into BigQuery.Read blog post
How to Load Salesforce Data Into Redshift
Getting your Salesforce data into your Redshift data warehouse is the first step in setting up a powerful analytical workflow and getting valuable insights from your data. Follow this tutorial to learn how to easily load your Salesforce data into Redshift.Read blog post
How to Load MongoDB Data Into BigQuery
Getting your MongoDB data into your BigQuery data warehouse is the first step in setting up a powerful analytical workflow and getting valuable insights from your data. Follow this tutorial to learn how to easily load your MongoDB data into BigQuery.Read blog post
How to Load Salesforce Data Into Snowflake
Getting your Salesforce data into your Snowflake is the first step in setting up a powerful analytical workflow and getting valuable insights from your data. Follow this tutorial to learn how to easily load your Salesforce data into Snowflake.Read blog post
What is Data Integration?
Data integration involves combining data from different sources while providing a unified view of the combined data, enabling you to query and manipulate all of your data from a single interface and derive analytics and statistics.Read blog post
Data Warehousing Tools
Data warehousing tools help you get all your data into one place, transform or enrich it, and then analyze it for important insights. Read on to learn more about the various types of tools that help make this complicated and important process possible.Read blog post
Incorporating ETL into Your Data Warehousing Strategy
Learn how automated ETL tools enable business intelligence by integrating with and facilitating ETL into your preferred data warehouse.Read blog post
What is Cloud Migration?
When companies move their data and applications from their premises to the cloud, this process is called cloud migration. The process may involve moving all your applications and services, or it may take a slower approach where some applications are moved to the cloud, while others remain on-premise. This approach is called a hybrid migration.Read blog post
What is Data Ingestion?
Data ingestion allows you to move your data from multiple different sources into one place so you can see the big picture hidden in your data.Read blog post
What is Data Cleansing?
The goal of data cleansing is to improve data quality and utility by catching and correcting errors before it is transferred to a target database or data warehouse.Read blog post
Data Warehouse Architecture: On-Premise vs. Cloud
To better understand how architecture plays a role in determining the right data warehouse solution, learn how on-premise and cloud-based warehouses are built and the level of upfront investment in people and resources that are required.Read blog post
Instantly Connect Your Data to Snowflake with Alooma
Snowflake and Alooma have teamed up to offer a seamless, fast, and trusted data integration solution to make going "from data to analysis" as quick and easy as possible.Read blog post
Choosing a Database: MySQL vs. MongoDB
Understand the key differences and similarities between MySQL and MongoDB.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
Deciding on a Data Warehouse: Cloud vs. On-Premise
Learn how on-premise and cloud data warehouses function differently from each other and the benefits each can provide to your business so you can arrive at the right solution.Read blog post
Moving Your Data to the Cloud: The Benefits of Cloud Migration
There’s a lot of buzz about moving to the cloud, but what are the real benefits? Let’s look a little more closely into the problems that migrating to the cloud can solve.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
Build vs. Buy — Solving Your Data Pipeline Problem
Learn about the challenges associated with building a data pipeline in-house and how an automated solution can deliver the flexibility, scale, and cost effectiveness that businesses demand when it comes to modernizing their data intelligence operations.Read blog post
What is a Data Pipeline?
A data pipeline allows you to consolidate data from multiple sources and makes it available for analysis and visualization.Read blog post
Data Integration Tools
Learn about the various types of data integration tools, including on-premise, open source, and cloud-based.Read blog post
What is a Data Warehouse?
A data warehouse is a large-capacity repository that sits on top of multiple databases and is designed to handle a variety of data sources, such as sales data, data from marketing automation, real-time transactions, SaaS applications, SDKs, APIs, and more.Read blog post
Database vs Data Warehouse
Learn the differences between databases and data warehouses and how each serves a different function within an organization.Read blog post
2019 ETL Tools Comparison
Trying to decide on the best ETL solution for your organization? Learn about the most popular incumbent batch and modern cloud-based ETL solutions and how they compare.Read blog post
Open Source ETL Tools Comparison
Open source ETL tools are a low cost alternative to commercial packaged solutions. Just like commercial solutions, they have their benefits and drawbacks. Learn about the advantages and disadvantages of the most widely known open source ETL tools.Read blog post
ETL Unleashes Competitive Advantage for the Gaming Industry
Dominating in the data-driven world of online gaming means surmounting numerous challenges, many of which can be effectively addressed with the help of a robust extract, transform, load (ETL) platform. Learn how Alooma can help game developers and publishers transform data into actionable insights.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 Types of Modern Databases
Choosing the best database management system for your organization can be a complex process. In this article, you'll learn about the two types of databases: NoSQL (non-relational) and Relational Database Management Systems (RDBMS) and key differentiators between them.Read blog post
How to Choose a Cloud Data Warehouse Solution
Choosing a modern cloud data warehouse can be tricky since they are all so similar. In this article, we will provide a guide of the factors you should use to evaluate such as use case, speed, cost, scalability, security and reliability. We’ll look at the most popular options: AWS Redshift, Google BigQuery, Snowflake, Azure, and S3.Read blog post
Migrate Oracle Data to the Cloud With Alooma
Learn how Alooma can easily help migrate your Oracle database to any cloud data warehouse so you can avoid the pitfalls of doing it yourself.Read blog post
Migrating Oracle Data to the Cloud With the Oracle LogMiner
Migrating Oracle data to the cloud is a complex and lengthy process. In this post, we look at the process and dive into the method of using Oracle LogMiner, which provides a view into the database change log. This is what Alooma uses to continuously replicate all changes to your Oracle data.Read blog post
Encrypt Private Health and Financial Data in Real-Time
It’s critical for health and financial organizations to protect patient and client data. But with so much data coming in, how do you safeguard it at scale? We’ll show you how you can use the Alooma Code Engine to encrypt all your data in real-time in just two steps.Read blog post
Using Snowflake Snowpipe to Optimize Data Throughput
Snowflake with Snowpipe: How Alooma uses Snowpipe to help you save money while transforming your business. Enable near real time data loading to ensure fresh data, but keep the lower cost of scheduled loading.Read blog post
ETL Testing: The Future is Here
The ETL testing process used to be arduous - learn how a modern ETL platform built for the cloud era can help test ETL at scale in only a few easy steps.Read blog post
Using Real-Time ETL to Improve Decisions
The next evolution of data-driven decisions is real-time data driven decisions. This is how winning businesses of today and the future will compete. For real-time data analysis and decisions to work at scale, they need to be cloud-based, use real-time stream processing and utilize business intelligence tools.Read blog post
Periscope Data Warehouse Now Supported
Alooma supports the new Periscope Data Warehouse as an output.Read blog post
Three Ways to Ingest Data Without a Native Connector
Three ways to ingest data through Alooma into a cloud data warehouse without a native integrationRead blog post
Best Practices for Migrating from On-Prem to Cloud
The advantages of migrating to the cloud are very clear and the industry is showing it. According to the IDC Worldwide Quarterly Cloud IT Infrastructure Tracker, deployment in cloud environments will increase by 18.2% in 2017 to $44.2 billion.Read blog post
How Redash is Helping Alooma Sustain a Data Driven Culture
Alooma and Redash share the same mission: to liberate data and unleash its full potential.Read blog post
Alooma’s Roundup of Snowflake’s Cloud Analytics City Tour
Alooma data pipeline service company recaps the 2017 Snowflake Cloud Analytics City TourRead blog post
Harness the power of Salesforce data with ETL
Extract, transform and load (ETL) your Salesforce data to BigQuery, Redshift or Snowflake to get the most out of your data.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
Solving The Challenges of Mapping Your Data
When mapping is done correctly, the pipeline process works smoothly with fewer loading errors. That’s why we at Alooma allow you to automate the mapping process, so you won’t have to deal with the dirty work of deciding which column should be mapped to which data type.Read blog post
Redshift Vacuum and Analyze Tool: Doing your Maintenance Work for you
Explaining why VACUUM and ANALYZE are required. We’re providing you with a free tool to manage your maintenance tasks.Read blog post
Redshift: How to alter column in 3 clicks
There’s no simple, native way to alter a column’s name or data type in Redshift, BigQuery, or Snowflake. So, we built one which enables you to alter a column in 3 clicks within the Alooma Platform. Read on to learn about how we, as a product team, got there.Read blog post
Infographic: Why Streaming Data Pipelines Matter
Streaming data pipelines today are enabling organizations to transform and become data-driven.Read blog post
Recruiting a Top Notch ETL Developer
In order to build a great data team, you need great data engineers. Here's how to hire them.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
Real-Time Anomaly Detection on the Stream
How to monitor and detect anomalies in KPIs in real time using Alooma’s Code Engine.Read blog post
Enriching Streaming Data With External Sources
How to use Alooma’s Code Engine to enrich streaming events with data from external sourcesRead blog post
ETL Tools: A Modern List
Extract, Transform and Load (ETL) tools enable organizations to make their data accessible, meaningful, and usable across disparate data systems. When it comes to choosing the right ETL tool, there are many options to choose from.Read blog post
Harnessing real-time data to improve customer experience
An example of how we at Alooma use real-time data collected from multiple sources to gain insight into our customer's actions, and to improve customer hapiness.Read blog post
Amazon Athena - Initial Analysis
Everything you need to know about Amazon's latest announcement: Amazon Athena - an interactive query service for Amazon S3.Read blog post
Alooma Live - Kafka Real-Time Visualization
Introducing Alooma Live - our new tool for real-time, big-data stream visualizationRead blog post
Forbes names Alooma the rising star of data infrastructure
Alooma is proud to be named the rising star of data infrastructure in the Forbes 2016 World’s Best Cloud Companies list.Read blog post
4 Valuable Resources on Stream processing
Beginner guide to stream processing. Statefull, Stateless and in between.Read blog post
Use webhooks to integrate data sources with Alooma
Use webhooks to integrate any SaaS product to your data warehouseRead blog post
Making big data analysis accessible throughout your company
How to make everyone at your company data driven, regardless of their SQL knowledge.Read blog post
Welcoming BigQuery, MySQL and MemSQL
Today we announce new data warehouse integrations to BigQuery, MySQL and MemSQLRead blog post
5 Valuable Resource on Custom Analytics
A mini-list of 5 brilliant blog posts on Custom AnalyticsRead blog post
MySQL to Amazon Redshift Replication
How to replicate your MySQL to Amazon Redshift: A comparison of 3 common approaches with detailed real-world examples.Read blog post
Amazon Redshift for Custom Analytics - Full Guide
Learn how to build a custom analytics pipeline over Amazon Redshift with real-world examples of engagement, funnels, retention and customer value analyses.Read blog post
Export Application Insights to Amazon Redshift with Alooma
Learn how to export Application Insights data to Amazon Redshift with AloomaRead blog post
Building a Professional Grade Data Pipeline
Flexible, reliable data pipelines are hard to build. We do this for a living, and wanted to share our knowledge and experience in understanding the difficulties.Read blog post
Building Dockers with Maven for Continuous Integration
How we at Alooma are building dockers using docker-maven-plugin and Jenkins.Read blog post
Exactly-Once Processing with Trident - The Fake Truth
Dissecting the Trident Guarantee of Exactly-Once SemanticsRead blog post
TLV Data Plumbers First Meetup
Data Plumbing Blues - The first data plumbers meetup with 3 Real-Life ExamplesRead blog post