Last updated: 28 September 2026. Pricing mechanics verified against AWS and Google Cloud documentation on that date. This article replaces a 2019 comparison at the same address.Quick answer:Amazon Redshift and Google BigQuery are both mature cloud data warehouses, and in…
Continue reading Redshift vs BigQuery: a full comparison (2026)
In the age of big data, companies rely on effective data processing methods to extract insights and make decisions that grow the business. One key process in this domain is the ETL data pipeline. Understanding ETL data pipelines and how…
Continue reading ETL Data Pipelines: Key Concepts and Best Practices
Data warehouses are becoming increasingly popular as many businesses, nonprofits, and municipal organizations realize the value of storing their current and historic data in a dynamic and useful way. The data warehouse is the central place where all of the different…
Continue reading Can PostgreSQL Work as a Data Warehouse? (2024 Updated)
Sometimes, the only thing standing between an analyst and a catastrophic management decision could be knowing the difference between the tables:_web\_user\_behavior\_v2_ and_web\_user\_behavior\_new_Effective naming conventions for your data warehouses allow data analysts to do an exponentially better job—but it’s far from…
Continue reading Data Warehouse Naming Conventions Guide: Best Practices (2024 updated)
Extracting meaningful, actionable insights from your data is critical to making informed decisions for your business. However, even with a managed solution, the process of querying your data often requires a deep understanding of SQL (Structured Query Language), posing a…
Continue reading Introducing Query Builder: Get Insights Faster, with Zero Code
Historical data is a record of past events, transactions, and activities systematically captured and stored over time. For small and medium-sized businesses (SMBs), understanding the significance of historical data within a data warehouse (DW) framework is crucial for unlocking valuable…
Continue reading The Role of Historical Data in a Data Warehouse: Insights and Strategies
Cloud-based data warehousing has emerged as a game-changer in the realm of data management, providing businesses with unparalleled advantages in terms of scalability, accessibility, and cost-efficiency. For small and medium-sized businesses (SMBs), as well as data analysts and management professionals,…
Continue reading Demystifying Cloud-Based Data Warehouses: Benefits and Considerations
Making data accessible can be a big hurdle to overcome. Luckily, Panoply makes it easy. No other platform makes syncing and storing data – without days of engineering work – so easy. However, once the data is accessible, a new…
Continue reading Looking at the Best Looker and LookerML Alternatives
Last month, VentureBeat published an article from our own Head of R&D, Dima Dobrinsky. In this piece, Dima discusses the AI tool boom and how businesses can accurately measure and improve success with now-ubiquitous AI tools like ChatGPT and Bard. Due…
Continue reading Around the World of AI with Panoply’s Head of R&D
For e-commerce SMBs, the holiday season represents a golden opportunity to boost sales and expand their customer base. However, with great opportunity comes great responsibility. The increased demand and heightened customer expectations can be overwhelming without a well-thought-out strategy, and…
Continue reading Empowering e-Commerce: Unwrap the Gift of Data Analysis this Holiday Season
Data democratization allows everyone in your business, regardless of their role or level of technical savvy, to access and use data as it relates to their role. A self-serve data model from a single source of truth is essential if…
Continue reading Democratize Your Data with a Data Warehouse
Are you struggling with connecting problematic data sources to your data warehouse? Don’t worry, you’re not alone, and it’s a common frustration data professionals mention when speaking with us about our managed data warehouse solution. At Panoply, we’re here to…
