nodejs-bigquery
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nodejs-bigquery
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Wrangling BigQuery at Reddit
If you've ever wondered what it's like to manage a BigQuery instance at Reddit scale, know that it's exactly like smaller systems just with much, much bigger numbers in the logs. Database management fundamentals are eerily similar regardless of scale or platform; BigQuery handles just about anything we throw at it, and we do indeed throw it the whole book. Our BigQuery platform is more than 100 petabytes of data that supports data science, machine learning, and analytics workloads that drive experiments, analytics, advertising, revenue, safety, and more. As Reddit grew, so did the workload velocity and complexity within BigQuery and thus the need for more elegant and fine-tuned workload management.
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Building a dev.to analytics dashboard using OpenSearch
Now I know I've got some data I could use, I now need to find a platform that I can use to analyse the data coming from the Forem API. I did consider some other pieces of software, such as Google BigQuery (with looker studio) and ElasticSearch (with Kibana), I ultimately went with OpenSearch which is essentially a forked version of ElasticSearch maintained by AWS. The main reasons are that I could host it locally for free (unlike BigQuery). I do have some prior experience with both elastic (back when it was called ELK) and OpenSearch, but my work with OpenSearch was far more recent, so I decided to go with that.
- Como evitar SQL Injection utilizando client do BigQuery
- Learning Excel. Is there a resource for fake data sets like retail and wholesale inventories and sales histories etc for testing and practice?
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How to Totally Fubar Your Cloud Infrastructure Costs
First, in one of our recent projects, we helped our client to run the cloud-based infrastructure of their entirely automated, real-time SEO platform. The solution rested in the safe familiarity of Googleโs popular cloud-based data centres (i.e. Google Cloud Platform), whilst also making use of BigQuery โ a serverless, multi-cloud data warehouse.
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Data Analytics at Potloc I: Making data integrity your priority with Elementary & Meltano
Bigquery as our data warehouse
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I've tried really hard but need some help please. Bigquery not returning data after 2019.
This post in github thinks it may be an error in bigquery's backend.
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Deploying a Data Warehouse with Pulumi and Amazon Redshift
A data warehouse is a specialized database that's purpose built for gathering and analyzing data. Unlike general-purpose databases like MySQL or PostgreSQL, which are designed to meet the real-time performance and transactional needs of applications, a data warehouse is designed to collect and process the data produced by those applications, collectively and over time, to help you gain insight from it. Examples of data-warehouse products include Snowflake, Google BigQuery, Azure Synapse Analytics, and Amazon Redshift โ all of which, incidentally, are easily managed with Pulumi.
- [Question] Which GCP tool should I use to build a Business decisional dashboard?
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Designing a Video Streaming Platform ๐น
Google BigQuery
dbt
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Open Source Analytics Stack: Bringing Control, Flexibility, and Data-Privacy to Your Analytics
Due to the rise in cloud-based data warehouses, businesses can directly load all the raw data into the data warehouse without prior transformations. This process is known as ELT (Extract, Load, Transform) and gives data and analytics teams freedom to develop ad-hoc transformations based on their particular needs. ELT became popular as the cloud's processing power and scale became better suited to transforming data. DBT (website, GitHub) is a popular open-source tool recommended for ELT and allows businesses to transform data in their warehouses more effectively. It's a great pairing with with RudderStack's Cloud Extract ETL tool.
What are some alternatives?
airbyte - The leading data integration platform for ETL / ELT data pipelines from APIs, databases & files to data warehouses, data lakes & data lakehouses. Both self-hosted and Cloud-hosted.
Apache Kafka - Mirror of Apache Kafka
dbt-core - dbt enables data analysts and engineers to transform their data using the same practices that software engineers use to build applications.
dagster - An orchestration platform for the development, production, and observation of data assets.
superset - Apache Superset is a Data Visualization and Data Exploration Platform
rudderstack-docs - Documentation repository for RudderStack - the Customer Data Platform for Developers.
Snowplow - The enterprise-grade behavioral data engine (web, mobile, server-side, webhooks), running cloud-natively on AWS and GCP
streamlit - Streamlit โ A faster way to build and share data apps.
nbdev - Create delightful software with Jupyter Notebooks
cube.js - ๐ Cube โ The Semantic Layer for Building Data Applications