Setting up Data Lake on GCP using Cloud Storage and BigQuery
Analytics Vidhya
FEBRUARY 25, 2023
The need for a data lake arises from the growing volume, variety, and velocity of data companies need to manage and analyze.
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4 Key Patterns to Load Data Into A Data Warehouse
Start Data Engineering
AUGUST 17, 2021
Batch Data Pipelines 1.1 Process => Data Warehouse 1.2 Process => Cloud Storage => Data Warehouse 2. Near Real-Time Data pipelines 2.1 Data Stream => Consumer => Data Warehouse 2.2
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Creating a Data Pipeline with Spark, Google Cloud Storage and Big Query
Towards Data Science
MARCH 6, 2023
On-premise and cloud working together to deliver a data product Photo by Toro Tseleng on Unsplash Developing a data pipeline is somewhat similar to playing with lego, you mentalize what needs to be achieved (the data requirements), choose the pieces (software, tools, platforms), and fit them together.
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Enabling Multi-User Fine-Grained Access Control for Cloud Storage in CDP
Cloudera
SEPTEMBER 10, 2021
Shared Data Experience ( SDX ) on Cloudera Data Platform ( CDP ) enables centralized data access control and audit for workloads in the Enterprise Data Cloud. The public cloud (CDP-PC) editions default to using cloud storage (S3 for AWS, ADLS-gen2 for Azure).
A Cost-Effective Data Warehouse Solution in CDP Public Cloud – Part1
Cloudera
FEBRUARY 9, 2021
Today’s customers have a growing need for a faster end to end data ingestion to meet the expected speed of insights and overall business demand. This ‘need for speed’ drives a rethink on building a more modern data warehouse solution, one that balances speed with platform cost management, performance, and reliability.
Cloudera Data Warehouse outperforms Azure HDInsight in TPC-DS benchmark
Cloudera
SEPTEMBER 29, 2020
Performance is one of the key, if not the most important deciding criterion, in choosing a Cloud Data Warehouse service. In today’s fast changing world, enterprises have to make data driven decisions quickly and for that they rely heavily on their data warehouse service. . benchmark.
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Data Warehouse Migration Best Practices
Monte Carlo
FEBRUARY 6, 2023
So, you’re planning a cloud data warehouse migration. But be warned, a warehouse migration isn’t for the faint of heart. As you probably already know if you’re reading this, a data warehouse migration is the process of moving data from one warehouse to another. A worthy quest to be sure.
Using Trino And Iceberg As The Foundation Of Your Data Lakehouse
Data Engineering Podcast
FEBRUARY 18, 2024
Summary A data lakehouse is intended to combine the benefits of data lakes (cost effective, scalable storage and compute) and data warehouses (user friendly SQL interface). Multiple open source projects and vendors have been working together to make this vision a reality.
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How to move data from spreadsheets into your data warehouse
dbt Developer Hub
NOVEMBER 22, 2022
Once your data warehouse is built out, the vast majority of your data will have come from other SaaS tools, internal databases, or customer data platforms (CDPs). Spreadsheets are the Swiss army knife of data processing. But there’s another unsung hero of the analytics engineering toolkit: the humble spreadsheet.
Data Lake vs. Data Warehouse: Differences and Similarities
U-Next
SEPTEMBER 7, 2022
The terms “ Data Warehouse ” and “ Data Lake ” may have confused you, and you have some questions. There are times when the data is structured , but it is often messy since it is ingested directly from the data source. What is Data Warehouse? . Data Warehouse in DBMS: .
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Data Lake vs Data Warehouse - Working Together in the Cloud
ProjectPro
AUGUST 11, 2021
“Data Lake vs Data Warehouse = Load First, Think Later vs Think First, Load Later” The terms data lake and data warehouse are frequently stumbled upon when it comes to storing large volumes of data. Data Warehouse Architecture What is a Data lake?
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Data Warehouse vs Data Lake vs Data Lakehouse: Definitions, Similarities, and Differences
Monte Carlo
AUGUST 25, 2023
At the same time, 81% of IT leaders say their C-suite has mandated no additional spending or a reduction of cloud costs. Data teams need to balance the need for robust, powerful data platforms with increasing scrutiny on costs. But, the options for data storage are evolving quickly. Let’s dive in.
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Altus Data Warehouse
Cloudera
SEPTEMBER 9, 2018
We are proud to announce the general availability of Cloudera Altus Data Warehouse , the only cloud data warehousing service that brings the warehouse to the data. Modern data warehousing for the cloud. Cloudera Altus Data Warehouse is designed with agile data teams in mind.
Why Open Table Format Architecture is Essential for Modern Data Systems
phData: Data Engineering
NOVEMBER 8, 2024
Versioning also ensures a safer experimentation environment, where data scientists can test new models or hypotheses on historical data snapshots without impacting live data. Note : Cloud Data warehouses like Snowflake and Big Query already have a default time travel feature. FAQs What is a Data Lakehouse?
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Redshift Datepart Function 101: Syntax and Usage Simplified
Hevo
JUNE 6, 2024
With the emergence of Cloud Data Warehouses, enterprises are gradually moving towards Cloud storage leaving behind their On-premise Storage systems. Amazon Web Services is one such Cloud Computing platform that offers Amazon Redshift as their Cloud Data Warehouse product. […]
Upgrade your Modern Data Stack
Christophe Blefari
SEPTEMBER 28, 2023
That's why big data technologies got swooshed by the modern data stack when it arrived on the market—excepting Spark. We jumped from HDFS to Cloud Storage (S3, GCS) for storage and from Hadoop, Spark to Cloud warehouses (Redshift, BigQuery, Snowflake) for processing. Cloud-first.
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Group vs Fine-Grained Access Control in Cloudera Data Platform Public Cloud
Cloudera
SEPTEMBER 28, 2021
Cloudera Data platform ( CDP ) provides a Shared Data Experience ( SDX ) for centralized data access control and audit in the Enterprise Data Cloud. The Ranger Authorization Service (RAZ) is a new service added to help provide fine-grained access control (FGAC) for cloud storage. Conclusion.
Cost Conscious Data Warehousing with Cloudera Data Platform
Cloudera
DECEMBER 10, 2020
Why worry about costs with cloud-native data warehousing? Have you been burned by the unexpected costs of a cloud data warehouse? If so, you know about the failed economics of some cloud-native solutions on the market today. These costs impede the adoption of cloud-native data warehouses.
DELL/EMC taking the next step with PowerScale and ECS certification on CDP Private Cloud Base
Cloudera
OCTOBER 26, 2020
Cloudera and Dell/EMC are continuing our long and successful partnership of developing shared storage solutions for analytic workloads running in hybrid cloud. . Since the inception of Cloudera Data Platform (CDP), Dell / EMC PowerScale and ECS have been highly requested solutions to be certified by Cloudera. Encryption.
Use Case for Loading Daily Feeds into Snowflake
Cloudyard
JUNE 16, 2024
These files need to be ingested into a data warehouse like Snowflake for further processing and analysis. Automating this process ensures data is consistently and reliably loaded without manual intervention. Suppose you are a data engineer at a company that receives daily sales data from an external vendor.
Get Your Analytics Insights Instantly – Without Abandoning Central IT
Cloudera
JANUARY 21, 2021
While cloud-native, point-solution data warehouse services may serve your immediate business needs, there are dangers to the corporation as a whole when you do your own IT this way. Of course you don’t want to re-create the risks and costs of data silos your organization has spent the last decade trying to eliminate.
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Top Data Lake Vendors (Quick Reference Guide)
Monte Carlo
APRIL 24, 2023
By accommodating various data types, reducing preprocessing overhead, and offering scalability, data lakes have become an essential component of modern data platforms , particularly those serving streaming or machine learning use cases. See our post: Data Lakes vs. Data Warehouses.
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8 Data Ingestion Tools (Quick Reference Guide)
Monte Carlo
FEBRUARY 20, 2024
Integrations : They offer a wide array of connectors for databases, SaaS applications, cloud storage solutions, and more, covering both popular and niche data sources. Batch vs Streaming : They focus on automated batch data integration but also support near real-time data replication for certain sources.
Introducing Compute-Compute Separation for Real-Time Analytics
Rockset
MARCH 1, 2023
If such query workloads create additional data lags then it will actively cause more harm by increasing your blind spot at the exact wrong time, the time when fraud is being perpetrated. OLTP databases aren’t built to ingest massive volumes of data streams and perform stream processing on incoming datasets.
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ThoughtSpot Sage: data security with large language models
ThoughtSpot
MAY 31, 2023
Architecture Let's start with the big picture and tackle how we adjusted our cloud architecture with additional internal and external interfaces to integrate LLM. Search and model assist hints are stored in the tenant specific cloud storage bucket.
When To Use Internal vs. External Stages in Snowflake
phData: Data Engineering
AUGUST 4, 2023
Data storage is a vital aspect of any Snowflake Data Cloud database. Within Snowflake, data can either be stored locally or accessed from other cloud storage systems. In Snowflake, there are three different storage layers available, Database, Stage, and Cloud Storage.
Rethinking Data Marts in the Cloud
Cloudera
OCTOBER 26, 2017
Become more agile with business intelligence and data analytics. Clouds (source: Pexels ). Many of us are all too familiar with the traditional way enterprises operate when it comes to on-premises data warehousing and data marts: the enterprise data warehouse (EDW) is often the center of the universe.
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AI Data Platform: Key Requirements for Fueling AI Initiatives
Ascend.io
FEBRUARY 23, 2024
Before we explore the specific requirements your AI data platform, let’s evaluate your technical foundation’s readiness for AI. Critical considerations include: Do you have the cloud capabilities necessary to scale with AI’s demands? Is your data environment diverse and accessible enough to fuel AI algorithms?
Google BigQuery: A Game-Changing Data Warehousing Solution
ProjectPro
JANUARY 24, 2023
With the global cloud data warehousing market likely to be worth $10.42 billion by 2026, cloud data warehousing is now more critical than ever. Cloud data warehouses offer significant benefits to organizations, including faster real-time insights, higher scalability, and lower overhead expenses.
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Fivetran Supports the Automation of the Modern Data Lake on Amazon S3
phData: Data Engineering
APRIL 4, 2023
Customers who don’t necessarily want to put their data directly into a data warehouse like the Snowflake Data Cloud can now use Fivetran to build a performant, governed, managed dataset on top of S3 which can still be efficiently queried and manipulated from within their query engine of choice.
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Moving Past ETL and ELT: Understanding the EtLT Approach
Ascend.io
AUGUST 31, 2023
In the dynamic world of data, many professionals are still fixated on traditional patterns of data warehousing and ETL, even while their organizations are migrating to the cloud and adopting cloud-native data services. Source : A stream of sensor data represented as a directed acyclic graph.
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Data Warehousing Guide: Fundamentals & Key Concepts
Monte Carlo
FEBRUARY 15, 2023
Since the inception of the cloud, there has been a massive push to store any and all data. On the surface, the promise of scaling storage and processing is readily available for databases hosted on AWS RDS, GCP cloud SQL and Azure to handle these new workloads. Cloud data warehouses solve these problems.
Accelerate your Data Migration to Snowflake
RandomTrees
SEPTEMBER 6, 2020
Snowflake Overview A data warehouse is a critical part of any business organization. Lot of cloud-based data warehouses are available in the market today, out of which let us focus on Snowflake. Snowflake is an analytical data warehouse that is provided as Software-as-a-Service (SaaS).
Demystifying Modern Data Platforms
Cloudera
SEPTEMBER 15, 2022
A key area of focus for the symposium this year was the design and deployment of modern data platforms. Luke: Let’s talk about some of the fundamentals of modern data architecture. What is a data fabric? Mark: Gartner states that a data fabric “enables frictionless access and sharing of data in a distributed data environment.”
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Ascending with MotherDuck
Ascend.io
JUNE 22, 2023
Ascend is thrilled to announce the availability of our newest feature: the ability to deliver data directly to the MotherDuck analytics platform! Get started with a free developer-tier Ascend Cloud environment and begin loading your data into MotherDuck today ( docs )!
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How ATB Financial is Utilizing Hybrid Cloud to Reduce the Time to Value for Big Data Analytics by 90 Percent
Cloudera
FEBRUARY 7, 2019
The company sought a data management platform that would allow its enterprise to handle greater data variety, velocity and volume in a cost-effective manner. Enabling this transformation is the HDP platform, along with SAS Viya on Google Cloud , which has delivered machine learning models and personalization at scale.
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Data Governance and Strategy for the Global Enterprise
Cloudera
SEPTEMBER 23, 2022
Modern data lakehouses are typically deployed in the cloud. Cloud computing brings several distinct advantages that are core to the lakehouse value proposition. The first is near unlimited storage. Leveraging cloud-based object storage frees analytics platforms from any storage constraints.
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Jobprofil des Data Engineers
Data Science Blog: Data Engineering
DECEMBER 23, 2022
Noch konkreter wird der Bedarf an Datenbeschaffung und -aufbereitung in der Business Intelligence, denn diese benötigt für nachhaltiges Reporting feste Strukturen wie etwa ein Data Warehouse. Abbildung 1 – Data Engineering ist der Mittelpunkt einer jeden Datenplattform.
A Definitive Guide to Using BigQuery Efficiently
Towards Data Science
MARCH 5, 2024
BigQuery basics and understanding costs BigQuery is not just a tool but a package of scalable compute and storage technologies, with fast network, everything managed by Google. At its core, BigQuery is a serverless Data Warehouse for analytical purposes and built-in features like Machine Learning ( BigQuery ML ).
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The Hidden Challenges of the Modern Data Stack
Ascend.io
MAY 18, 2023
What we think of as “the modern data stack” today is an evolution of the traditional data stack that can be traced back to physical servers that companies kept on-prem, collecting and storing data that would drive innovation over decades. While this on-prem stack of tools worked, it wasn’t ideal.
Export BigQuery Table to CSV: 3 Easy Methods
Hevo
MAY 8, 2023
The exponential rate of data generation in every modern business from various SaaS applications, Marketing Channels, etc. has compelled them to move from On-premise databases to Cloud-Based Data Warehouses.
50 Cloud Computing Interview Questions and Answers for 2023
ProjectPro
JULY 30, 2021
Why Learn Cloud Computing Skills? The job market in cloud computing is growing every day at a rapid pace. A quick search on Linkedin shows there are over 30000 freshers jobs in Cloud Computing and over 60000 senior-level cloud computing job roles. What is Cloud Computing? Thus came in the picture, Cloud Computing.
Azure for Data Science: Overview, Challenges, Technologies
Knowledge Hut
NOVEMBER 16, 2023
Cloud computing, along with data science has been the buzzword for quite some time now. Companies have moved towards cloud architecture for their data storage and computing needs. There are some renowned cloud players like Amazon Web Services, Google Cloud, IBM Watson, etc.,
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Open Source Object Storage For All Of Your Data
Data Engineering Podcast
SEPTEMBER 22, 2019
Summary Object storage is quickly becoming the unifying layer for data intensive applications and analytics. Modern, cloud oriented data warehouses and data lakes both rely on the durability and ease of use that it provides. How do you approach project governance and sustainability?
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