phData

AUGUST 9, 2023

With ELT, we first extract data from source systems, then load the raw data directly into the data warehouse before finally applying transformations natively within the data warehouse. This is unlike the more traditional ETL method, where data is transformed before loading into the data warehouse.

ETL 52

ETL Data Warehouse Cloud Data Big Data 52

phData

SEPTEMBER 26, 2023

Sources The sources involved could influence or determine the options available for the data ingestion tool(s). These could include other databases, data lakes, SaaS applications (e.g. Data flows from the current data platform to the destination. The necessary access is granted so data flows without issue.

SQL 52

SQL Database ETL Data Modeling 52

ODSC - Open Data Science

JUNE 12, 2023

Then we have some other ETL processes to constantly land the past 5 years of data into the Datamarts. Then we have some other ETL processes to constantly land the past 5 years of data into the Datamarts. No-code/low-code experience using a diagram view in the data preparation layer similar to Dataflows.

Power BI 52

Power BI Data Warehouse ETL Data Preparation 52

Flipboard

JUNE 26, 2023

Companies are faced with the daunting task of ingesting all this data, cleansing it, and using it to provide outstanding customer experience. Typically, companies ingest data from multiple sources into their data lake to derive valuable insights from the data.

AWS 92

AWS ML ML ETL 92

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

Pickl AI

JULY 6, 2023

Hive is a data warehousing infrastructure built on top of Hadoop. It has the following features: It facilitates querying, summarizing, and analyzing large datasets Hadoop also provides a SQL-like language called HiveQL Hive allows users to write queries to extract valuable insights from structured and semi-structured data stored in Hadoop.

Hadoop 52

Hadoop SQL Big Data Big Data 52

ODSC - Open Data Science

APRIL 3, 2023

Skills like effective verbal and written communication will help back up the numbers, while data visualization (specific frameworks in the next section) can help you tell a complete story. Data Wrangling: Data Quality, ETL, Databases, Big Data The modern data analyst is expected to be able to source and retrieve their own data for analysis.

Analytics 52

Analytics Analytics Data Analyst SQL 52

ODSC - Open Data Science

JANUARY 18, 2024

So as you take inventory of your existing skill set, you’ll want to start to identify the areas where you need to focus on to become a data engineer. These areas may include SQL, database design, data warehousing, distributed systems, cloud platforms (AWS, Azure, GCP), and data pipelines. Learn more about the cloud.

Data Engineering 52

Data Engineering Data Engineer Data Engineering Data Engineering 52

Pickl AI

APRIL 6, 2023

Data Warehousing concepts and knowledge should be strong. Having experience using at least one end-to-end Azure data lake project. Strong skills in working with Azure cloud-based environment with delta lake implementation. Hands-on experience working with SQLDW and SQL-DB. What is Polybase?

Azure 52

Azure Data Engineering Data Engineer Data Engineering 52

The MLOps Blog

JANUARY 23, 2023

These tools may have their own versioning system, which can be difficult to integrate with a broader data version control system. For instance, our data lake could contain a variety of relational and non-relational databases, files in different formats, and data stored using different cloud providers. DVC Git LFS neptune.ai

ML 52

ML ML Data Lakes Machine Learning 52

IBM Journey to AI blog

JANUARY 5, 2023

The first generation of data architectures represented by enterprise data warehouse and business intelligence platforms were characterized by thousands of ETL jobs, tables, and reports that only a small group of specialized data engineers understood, resulting in an under-realized positive impact on the business.

Data Quality 52

Data Quality Data Lakes Data Warehouse Business Intelligence 52

The MLOps Blog

MARCH 15, 2023

Data Processing : You need to save the processed data through computations such as aggregation, filtering and sorting. Data Storage : To store this processed data to retrieve it over time – be it a data warehouse or a data lake. Uses secure protocols for data security.

Data Pipeline 59

Data Pipeline ETL SQL Data Quality 59

Tableau

MARCH 30, 2021

we’ve added new connectors to help our customers access more data in Azure than ever before: an Azure SQL Database connector and an Azure Data Lake Storage Gen2 connector. As our customers increasingly adopt the cloud, we continue to make investments that ensure they can access their data anywhere. March 30, 2021.

Azure 99

Azure Tableau Data Lakes SQL 99

phData

FEBRUARY 14, 2023

Qlik Replicate Qlik Replicate is a data integration tool that supports a wide range of source and target endpoints with configuration and automation capabilities that can give your organization easy, high-performance access to the latest and most accurate data. Replication of calculated values is not supported during Change Processing.

Data Warehouse 59

Data Warehouse Azure AWS Database 59

Tableau

MARCH 29, 2021

we’ve added new connectors to help our customers access more data in Azure than ever before: an Azure SQL Database connector and an Azure Data Lake Storage Gen2 connector. As our customers increasingly adopt the cloud, we continue to make investments that ensure they can access their data anywhere. March 30, 2021.

Azure 52

Azure Tableau Data Lakes SQL 52

phData

SEPTEMBER 28, 2023

Power BI Dataflows provide vital functionalities that effectively empower users to cleanse and reshape data from various sources. These Dataflows are crucial in fostering consistency and reducing the duplication of repetitive ETL (Extract, Transform, Load) steps, achieved by reusing transformations.

Power BI 78

Power BI Data Preparation Machine Learning Machine Learning 78

IBM Journey to AI blog

JANUARY 18, 2023

In another decade, the internet and mobile started the generate data of unforeseen volume, variety and velocity. It required a different data platform solution. Hence, Data Lake emerged, which handles unstructured and structured data with huge volume. Data lakehouse was created to solve these problems.

Data Lakes 52

Data Lakes Data Warehouse Azure Apache Hadoop 52

phData

FEBRUARY 5, 2024

The tool converts the templated configuration into a set of SQL commands that are executed against the target Snowflake environment. Replicate can interact with a wide variety of databases, data warehouses, and data lakes (on-premise or based in the cloud). It is also a helpful tool for learning a new SQL dialect.

SQL 52

SQL Database Data Quality Data Warehouse 52

IBM Journey to AI blog

MARCH 14, 2024

Db2 Warehouse fully supports open formats such as Parquet, Avro, ORC and Iceberg table format to share data and extract new insights across teams without duplication or additional extract, transform, load (ETL). This allows you to scale all analytics and AI workloads across the enterprise with trusted data. 

AWS 82

AWS Database AI AI 82

AWS Machine Learning Blog

AUGUST 21, 2023

You can streamline the process of feature engineering and data preparation with SageMaker Data Wrangler and finish each stage of the data preparation workflow (including data selection, purification, exploration, visualization, and processing at scale) within a single visual interface.

AWS 84

AWS Data Lakes Clustering Data Preparation 84

The MLOps Blog

OCTOBER 20, 2023

Example template for an exploratory notebook | Source: Author How to organize code in Jupyter notebook For exploratory tasks, the code to produce SQL queries, pandas data wrangling, or create plots is not important for readers. in a pandas DataFrame) but in the company’s data warehouse (e.g., documentation.

SQL 52

SQL Database Data Scientist Python 52

IBM Journey to AI blog

JULY 17, 2023

Watsonx.data is built on 3 core integrated components: multiple query engines, a catalog that keeps track of metadata, and storage and relational data sources which the query engines directly access. Watsonx.data allows customers to augment data warehouses such as Db2 Warehouse and Netezza and optimize workloads for performance and cost.

AI 66

AI AI Machine Learning Machine Learning 66

Flipboard

DECEMBER 18, 2023

He highlights innovations in data, infrastructure, and artificial intelligence and machine learning that are helping AWS customers achieve their goals faster, mine untapped potential, and create a better future. Learn more about the AWS zero-ETL future with newly launched AWS databases integrations with Amazon Redshift.

AWS 112

AWS Data Warehouse ETL SQL 112

IBM Journey to AI blog

AUGUST 4, 2023

By leveraging data services and APIs, a data fabric can also pull together data from legacy systems, data lakes, data warehouses and SQL databases, providing a holistic view into business performance. Then, it applies these insights to automate and orchestrate the data lifecycle.

Data Lakes 63

Data Lakes AI AI Data Governance 63

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 91

Data Lakes Analytics Analytics Clustering 91