Flipboard

NOVEMBER 27, 2024

While customers can perform some basic analysis within their operational or transactional databases, many still need to build custom data pipelines that use batch or streaming jobs to extract, transform, and load (ETL) data into their data warehouse for more comprehensive analysis.

ETL 138

ETL Data Warehouse Analytics Analytics 138

Data Science Blog

MAY 20, 2024

Enter AnalyticsCreator AnalyticsCreator, a powerful tool for data management, brings a new level of efficiency and reliability to the CI/CD process. It offers full BI-Stack Automation, from source to data warehouse through to frontend. It supports a holistic data model, allowing for rapid prototyping of various models.

Data Pipeline 262

Data Pipeline Data Warehouse Azure Data Lakes 262

databricks

MAY 3, 2023

Caching is an essential technique for improving the performance of data warehouse systems by avoiding the need to recompute or fetch the same.

Data Warehouse 263

Data Warehouse SQL 263

Pickl AI

DECEMBER 15, 2024

Summary : This guide provides an in-depth look at the top data warehouse interview questions and answers essential for candidates in 2025. Covering key concepts, techniques, and best practices, it equips you with the knowledge needed to excel in interviews and demonstrates your expertise in data warehousing.

Data Warehouse 52

Data Warehouse ETL Database Data Quality 52

databricks

MARCH 6, 2024

This blog continues our series looking at advancements from 2023 to the serverless data warehouse Databricks SQL. The best data warehouse is.

SQL 130

SQL Data Warehouse 130

Data Science Dojo

FEBRUARY 1, 2023

Introduction Dedicated SQL pools offer fast and reliable data import and analysis, allowing businesses to access accurate insights while optimizing performance and reducing costs. DWUs (Data Warehouse Units) can customize resources and optimize performance and costs.

Azure 195

Azure SQL Analytics Analytics 195

databricks

JUNE 14, 2023

It's been only 18 months since we announced Databricks SQL general availability - the serverless data warehouse on the Lakehouse - and we.

SQL 130

SQL Data Warehouse AI AI 130

Data Science Dojo

MARCH 27, 2025

Thats where data normalization comes in. Its a structured process that organizes data to reduce redundancy and improve efficiency. Whether you’re working with relational databases, data warehouses , or machine learning pipelines, normalization helps maintain clean, accurate, and optimized datasets. Simple, right?

Database 195

Database Data Warehouse Machine Learning Machine Learning 195

AWS Machine Learning Blog

APRIL 16, 2024

In the process of working on their ML tasks, data scientists typically start their workflow by discovering relevant data sources and connecting to them. They then use SQL to explore, analyze, visualize, and integrate data from various sources before using it in their ML training and inference.

SQL 115

SQL AWS Database Data Scientist 115

Data Science Blog

JULY 20, 2024

Es bietet vollständige Automatisierung des BI-Stacks und unterstützt ein breites Spektrum an Data Warehouses, analytischen Datenbanken und Frontends. Automatisierung: Erstellt SQL-Code, DACPAC-Dateien, SSIS-Pakete, Data Factory-ARM-Vorlagen und XMLA-Dateien. Data Lakes: Unterstützt MS Azure Blob Storage.

Azure 130

Azure SQL Power BI Data Lakes 130

Data Science Blog

MAY 15, 2023

tl;dr Ein Data Lakehouse ist eine moderne Datenarchitektur, die die Vorteile eines Data Lake und eines Data Warehouse kombiniert. Organisationen können je nach ihren spezifischen Bedürfnissen und Anforderungen zwischen einem Data Warehouse und einem Data Lakehouse wählen.

Data Warehouse 147

Data Warehouse Data Lakes Azure AWS 147

Data Science Connect

JANUARY 27, 2023

In this blog post, we will be discussing 7 tips that will help you become a successful data engineer and take your career to the next level. Learn SQL: As a data engineer, you will be working with large amounts of data, and SQL is the most commonly used language for interacting with databases.

Data Engineering 130

Data Engineering Data Engineering Data Engineering Data Engineer 130

Flipboard

DECEMBER 11, 2024

Organizations are building data-driven applications to guide business decisions, improve agility, and drive innovation. Many of these applications are complex to build because they require collaboration across teams and the integration of data, tools, and services. The following screenshot shows an example of the unified notebook page.

SQL 160

SQL AWS Data Lakes AI 160

IBM Journey to AI blog

APRIL 24, 2023

Data is reported from one central repository, enabling management to draw more meaningful business insights and make faster, better decisions. By running reports on historical data, a data warehouse can clarify what systems and processes are working and what methods need improvement.

Data Warehouse 112

Data Warehouse Data Lakes Database Big Data 112

Pickl AI

NOVEMBER 15, 2023

Discover the nuanced dissimilarities between Data Lakes and Data Warehouses. Data management in the digital age has become a crucial aspect of businesses, and two prominent concepts in this realm are Data Lakes and Data Warehouses. It acts as a repository for storing all the data.

Data Lakes 52

Data Lakes Data Warehouse Database ETL 52

AWS Machine Learning Blog

APRIL 3, 2025

This tool democratizes data access across the organization, enabling even nontechnical users to gain valuable insights. A standout application is the SQL-to-natural language capability, which translates complex SQL queries into plain English and vice versa, bridging the gap between technical and business teams.

AWS 74

AWS Data Governance Data Silos SQL 74

phData

JULY 10, 2024

Sigma Computing , a cloud-based analytics platform, helps data analysts and business professionals maximize their data with collaborative and scalable analytics. One of Sigma’s key features is its support for custom SQL queries and CSV file uploads. These tools allow users to handle more advanced data tasks and analyses.

SQL 52

SQL Data Warehouse Analytics Analytics 52

Smart Data Collective

SEPTEMBER 8, 2021

The ETL process is defined as the movement of data from its source to destination storage (typically a Data Warehouse) for future use in reports and analyzes. The data is initially extracted from a vast array of sources before transforming and converting it to a specific format based on business requirements. Conclusion.

ETL 126

ETL Hadoop Data Warehouse Data Pipeline 126

Smart Data Collective

JUNE 6, 2021

Google BigQuery is a service (within the Google Cloud platform (GCP)) implemented to collect and analyze big data (also known as a data warehouse). It was released in 2011 and praised for its serverless architecture that enables highly scalable and fast-provided structured query language (SQL) analytics. What is Big Data?”

Big Data Analytics 137

Big Data Analytics Big Data Analytics Big Data Big Data 137

AWS Machine Learning Blog

DECEMBER 29, 2022

Many of the RStudio on SageMaker users are also users of Amazon Redshift , a fully managed, petabyte-scale, massively parallel data warehouse for data storage and analytical workloads. It makes it fast, simple, and cost-effective to analyze all your data using standard SQL and your existing business intelligence (BI) tools.

AWS 128

AWS Machine Learning Machine Learning Natural Language Processing 128

AWS Machine Learning Blog

AUGUST 20, 2024

Natural language is ambiguous and imprecise, whereas data adheres to rigid schemas. For example, SQL queries can be complex and unintuitive for non-technical users. Handling complex queries involving multiple tables, joins, and aggregations makes it difficult to interpret user intent and translate it into correct SQL operations.

SQL 115

SQL AWS Database Natural Language Processing 115

phData

NOVEMBER 4, 2024

Snowflake excels in efficient data storage and governance, while Dataiku provides the tooling to operationalize advanced analytics and machine learning models. Together they create a powerful, flexible, and scalable foundation for modern data applications.

Machine Learning 69

Machine Learning Machine Learning Data Science ML 69

AWS Machine Learning Blog

DECEMBER 16, 2024

Now they can access databases and data warehouses, as well as unstructured business data, like emails, reports, charts, graphs, and images. Access all your data whether its stored in data lakes, data warehouses, third-party or federated data sources.

AWS 88

AWS AI AI Data Warehouse 88

Data Science Blog

SEPTEMBER 3, 2024

Während vor zehn Jahren ich für Celonis noch eine Installation erst einer MS SQL Server Datenbank, etwas später dann bevorzugt eine SAP Hana Datenbank auf einem on-prem Server beim Kunden voraussetzend installieren musste, bevor ich dann zur Installation der Celonis ServerAnwendung selbst kam, ist es heute eine 100% externe Cloud-Lösung.

Data Science 130

Data Science Power BI Azure Data Warehouse 130

IBM Data Science in Practice

JANUARY 13, 2025

The blog post explains how the Internal Cloud Analytics team leveraged cloud resources like Code-Engine to improve, refine, and scale the data pipelines. Background One of the Analytics teams tasks is to load data from multiple sources and unify it into a data warehouse. Thus, it has only a minimal footprint.

ETL 100

ETL Data Pipeline Database Data Warehouse 100

IBM Journey to AI blog

SEPTEMBER 11, 2023

Codd published his famous paper “ A Relational Model of Data for Large Shared Data Banks.” Boyce to create Structured Query Language (SQL). Developers can leverage features like REST APIs, JSON support and enhanced SQL compatibility to easily build cloud-native applications. Chamberlin and Raymond F.

Database 101

Database SQL Data Warehouse Machine Learning 101

Flipboard

AUGUST 17, 2023

Amazon Redshift is the most popular cloud data warehouse that is used by tens of thousands of customers to analyze exabytes of data every day. You can use query_string to filter your dataset by SQL and unload it to Amazon S3. If you’re familiar with SageMaker and writing Spark code, option B could be your choice.

ML 123

ML ML AWS Data Warehouse 123

IBM Journey to AI blog

MAY 9, 2023

Watsonx.data will allow users to access their data through a single point of entry and run multiple fit-for-purpose query engines across IT environments. Through workload optimization an organization can reduce data warehouse costs by up to 50 percent by augmenting with this solution. [1]

Data Warehouse 92

Data Warehouse AWS AI AI 92

phData

MARCH 8, 2023

Fivetran, a cloud-based automated data integration platform, has emerged as a leading choice among businesses looking for an easy and cost-effective way to unify their data from various sources. Fivetran is used by businesses to centralize data from various sources into a single, comprehensive data warehouse.

Data Warehouse 96

Data Warehouse Data Engineering Data Engineering Data Engineering 96

phData

APRIL 29, 2024

In our previous blog, Top 5 Fivetran Connectors for Financial Services , we explored Fivetran’s capabilities that address the data integration needs of the finance industry. Now, let’s cover the healthcare industry, which also has a surging demand for data and analytics, along with the underlying processes to make it happen.

SQL 52

SQL Data Warehouse Azure Cloud Data 52

Pickl AI

OCTOBER 6, 2024

Summary: This blog explores the key differences between ETL and ELT, detailing their processes, advantages, and disadvantages. Understanding these methods helps organizations optimize their data workflows for better decision-making. It ensures the data is accurate and reliable, leading to better decision-making.

ETL 52

ETL Data Warehouse Data Quality Data Lakes 52

AWS Machine Learning Blog

JUNE 13, 2023

The natural language capabilities allow non-technical users to query data through conversational English rather than complex SQL. The AI and language models must identify the appropriate data sources, generate effective SQL queries, and produce coherent responses with embedded results at scale.

Database 90

Database SQL AWS AI 90

phData

NOVEMBER 8, 2024

Open Table Format (OTF) architecture now provides a solution for efficient data storage, management, and processing while ensuring compatibility across different platforms. In this blog, we will discuss: What is the Open Table format (OTF)? Delta Lake became popular for making data lakes more reliable and easy to manage.

Data Lakes 52

Data Lakes Data Warehouse Database Azure 52

phData

JULY 17, 2023

Over the past few decades, the corporate data landscape has changed significantly. The shift from on-premise databases and spreadsheets to the modern era of cloud data warehouses and AI/ LLMs has transformed what businesses can do with data. Designed to cheaply and efficiently process large quantities of data.

Data Warehouse 52

Data Warehouse Data Pipeline Cloud Data ETL 52

Hacker News

AUGUST 27, 2024

Policy Zones has been built into different Meta systems, including: Function-based systems that load, process, and propagate data through stacks of function calls in different programming languages. Batch-processing systems that process data rows in batch (mainly via SQL ). When data flows across different systems (e.g.,

Data Warehouse 168

Data Warehouse Database SQL Machine Learning 168

IBM Journey to AI blog

SEPTEMBER 25, 2023

Every day, millions of riders use the Uber app, unwittingly contributing to a complex web of data-driven decisions. This blog takes you on a journey into the world of Uber’s analytics and the critical role that Presto, the open source SQL query engine, plays in driving their success. What is Presto?

Data Lakes 102

Data Lakes Analytics Analytics Clustering 102

phData

SEPTEMBER 2, 2024

In this blog, we will cover the best practices for developing jobs in Matillion, an ETL/ELT tool built specifically for cloud database platforms. The blog will be divided into three broad sections: Design, SDLC, and Security, each with its best practices. What Are Matillion Jobs and Why Do They Matter? Below are the best practices.

ETL 52

ETL Data Warehouse SQL Database 52