Flipboard

NOVEMBER 24, 2023

This use case highlights how large language models (LLMs) are able to become a translator between human languages (English, Spanish, Arabic, and more) and machine interpretable languages (Python, Java, Scala, SQL, and so on) along with sophisticated internal reasoning. Room for improvement!

Database 159

Database AWS ETL SQL 159

Pickl AI

NOVEMBER 4, 2024

Each database type requires its specific driver, which interprets the application’s SQL queries and translates them into a format the database can understand. The driver manages the connection to the database, processes SQL commands, and retrieves the resulting data. INSERT : Add new records to a table.

Database 52

Database SQL ETL Azure 52

Flipboard

JUNE 26, 2023

Transform raw insurance data into CSV format acceptable to Neptune Bulk Loader , using an AWS Glue extract, transform, and load (ETL) job. Run an AWS Glue ETL job to merge the raw property and auto insurance data into one dataset and catalog the merged dataset. Under Data classification tools, choose Record Matching.

AWS 123

AWS ML ML ETL 123

Data Science Dojo

JULY 3, 2024

Databases and SQL : Managing and querying relational databases using SQL, as well as working with NoSQL databases like MongoDB. Data Engineering : Building and maintaining data pipelines, ETL (Extract, Transform, Load) processes, and data warehousing.

Data Science 150

Data Science Machine Learning Machine Learning Data Visualization 150

AWS Machine Learning Blog

FEBRUARY 21, 2025

Apache Hive was used to provide a tabular interface to data stored in HDFS, and to integrate with Apache Spark SQL. The diagram depicts the flow; the key components are detailed below: Data Ingestion: Data is ingested into the system using Attunity data ingestion in Spark SQL. Analytic data is stored in Amazon Redshift.

Data Science 73

Data Science AWS Hadoop Data Scientist 73

IBM Journey to AI blog

MARCH 14, 2024

Businesses face significant hurdles when preparing data for artificial intelligence (AI) applications. 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).

AWS 93

AWS Database ETL AI 93

AWS Machine Learning Blog

JANUARY 17, 2024

To obtain such insights, the incoming raw data goes through an extract, transform, and load (ETL) process to identify activities or engagements from the continuous stream of device location pings. As part of the initial ETL, this raw data can be loaded onto tables using AWS Glue.

Clustering 131

Clustering AWS ML ML 131

AWS Machine Learning Blog

SEPTEMBER 18, 2024

The ZMP analyzes billions of structured and unstructured data points to predict consumer intent by using sophisticated artificial intelligence (AI) to personalize experiences at scale. Though it’s worth mentioning that Airflow isn’t used at runtime as is usual for extract, transform, and load (ETL) tasks.

AWS 120

AWS Machine Learning Machine Learning ML 120

Pickl AI

JULY 25, 2023

They create data pipelines, ETL processes, and databases to facilitate smooth data flow and storage. With expertise in programming languages like Python , Java , SQL, and knowledge of big data technologies like Hadoop and Spark, data engineers optimize pipelines for data scientists and analysts to access valuable insights efficiently.

Data Engineering 52

Data Engineering Data Engineer Data Engineering Data Engineering 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. Power BI Datamarts provide no-code/low-code datamart capabilities using Azure SQL Database technology in the background.

Power BI 52

Power BI Data Warehouse ETL Data Preparation 52

IBM Journey to AI blog

SEPTEMBER 25, 2023

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. This allowed them to focus on SQL-based query optimization to the nth degree. What is Presto?

Data Lakes 102

Data Lakes Analytics Analytics Clustering 102

Applied Data Science

AUGUST 2, 2021

The most common data science languages are Python and R   —  SQL is also a must have skill for acquiring and manipulating data. They build production-ready systems using best-practice containerisation technologies, ETL tools and APIs. The Data Engineer Not everyone working on a data science project is a data scientist.

Data Science 130

Data Science Data Scientist ML ML 130

AWS Machine Learning Blog

JUNE 25, 2024

Amazon Bedrock , a fully managed service designed to facilitate the integration of LLMs into enterprise applications, offers a choice of high-performing LLMs from leading artificial intelligence (AI) companies like Anthropic, Mistral AI, Meta, and Amazon through a single API.

AWS 126

AWS Natural Language Processing Machine Learning Machine Learning 126

ODSC - Open Data Science

APRIL 3, 2023

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. Competence in data quality, databases, and ETL (Extract, Transform, Load) are essential. SQL excels with big data and statistics, making it important in order to query databases.

Analytics 52

Analytics Analytics Data Analyst Data Science 52

Alation

JANUARY 17, 2023

Reverse ETL tools. Business intelligence (BI) platforms. The modern data stack is also the consequence of a shift in analysis workflow, fromextract, transform, load (ETL) to extract, load, transform (ELT). A Note on the Shift from ETL to ELT. In the past, data movement was defined by ETL: extract, transform, and load.

Data Warehouse 52

Data Warehouse ETL Tableau Cloud Data 52

Pickl AI

APRIL 26, 2024

It covers essential topics such as SQL queries, data visualization, statistical analysis, machine learning concepts, and data manipulation techniques. Key Takeaways SQL Mastery: Understand SQL’s importance, join tables, and distinguish between SELECT and SELECT DISTINCT. How do you join tables in SQL?

Data Analyst 52

Data Analyst Data Analysis Data Analysis Machine Learning 52

ODSC - Open Data Science

SEPTEMBER 27, 2023

Data Warehouses Some key characteristics of data warehouses are as follows: Data Type: Data warehouses primarily store structured data that has undergone ETL (Extract, Transform, Load) processing to conform to a specific schema. Processing: Relational databases are optimized for transactional processing and structured queries using SQL.

Data Lakes 98

Data Lakes Data Warehouse Database Big Data 98

AWS Machine Learning Blog

OCTOBER 9, 2024

Using Amazon Redshift ML for anomaly detection Amazon Redshift ML makes it easy to create, train, and apply machine learning models using familiar SQL commands in Amazon Redshift data warehouses. To use this feature, you can write rules or analyzers and then turn on anomaly detection in AWS Glue ETL.

AWS 91

AWS ML ML Data Quality 91

Pickl AI

SEPTEMBER 19, 2024

It also supports ETL (Extract, Transform, Load) processes, making data warehousing and analytics essential. Spark SQL Spark SQL is a module that works with structured and semi-structured data. It allows users to run SQL queries, read data from different sources, and seamlessly integrate with Spark’s core capabilities.

Hadoop 52

Hadoop Big Data Big Data Clustering 52

ODSC - Open Data Science

JANUARY 18, 2024

These areas may include SQL, database design, data warehousing, distributed systems, cloud platforms (AWS, Azure, GCP), and data pipelines. ETL (Extract, Transform, Load) This is a core data engineering process for moving data from one or more sources to a destination, typically a data warehouse or data lake.

Data Engineering 52

Data Engineering Data Engineer Data Engineering Data Engineering 52

IBM Journey to AI blog

AUGUST 4, 2023

An architecture designed for data democratization aims to be flexible, integrated, agile and secure to enable the use of data and artificial intelligence (AI) at scale. It’s distributed both in the cloud and on-premises, allowing extensive use and movement across clouds, apps and networks, as well as stores of data at rest.

Data Lakes 73

Data Lakes AI AI Data Governance 73

IBM Journey to AI blog

JULY 17, 2023

The next generation of Db2 Warehouse SaaS and Netezza SaaS on AWS fully support open formats such as Parquet and Iceberg table format, enabling the seamless combination and sharing of data in watsonx.data without the need for duplication or additional ETL.

AI 74

AI AI Machine Learning Machine Learning 74

IBM Journey to AI blog

JANUARY 18, 2023

They defined it as : “ A data lakehouse is a new, open data management architecture that combines the flexibility, cost-efficiency, and scale of data lakes with the data management and ACID transactions of data warehouses, enabling business intelligence (BI) and machine learning (ML) on all data. ”.

Data Lakes 52

Data Lakes Data Warehouse Azure Apache Hadoop 52

AWS Machine Learning Blog

AUGUST 21, 2023

Our customers wanted the ability to connect to Amazon EMR to run ad hoc SQL queries on Hive or Presto to query data in the internal metastore or external metastore (such as the AWS Glue Data Catalog ), and prepare data within a few clicks. When you’re connected, you can interactively view a database tree and table preview or schema.

AWS 97

AWS Data Lakes Clustering Data Preparation 97

Pickl AI

MARCH 10, 2025

Key Features Data Import: Connects to multiple data sources like Excel, SQL Server, or cloud services. Power Query Power Query is a powerful ETL (Extract, Transform, Load) tool within Power BI that helps users clean and transform raw data into usable formats. Impact: Scales seamlessly as organisational data grows.

Power BI 52

Power BI Business Intelligence Business Intelligence Analytics 52

AWS Machine Learning Blog

JANUARY 6, 2023

The rules in this engine were predefined and written in SQL, which aside from posing a challenge to manage, also struggled to cope with the proliferation of data from TR’s various integrated data source. Prior to building this centralized platform, TR had a legacy rules-based engine to generate renewal recommendations.

AWS 86

AWS Data Warehouse ML ML 86

ODSC - Open Data Science

SEPTEMBER 29, 2023

Spark is more focused on data science, ingestion, and ETL, while HPCC Systems focuses on ETL and data delivery and governance. It’s not a widely known programming language like Java, Python, or SQL. ECL sounds compelling, but it is a new programming language and has fewer users than languages like Python or SQL.

Data Lakes 52

Data Lakes Clustering Big Data Big Data 52

Pickl AI

DECEMBER 16, 2024

Data Factory : Simplifies the creation of ETL pipelines to integrate data from diverse sources. These features include: Data Connectivity : Connects to various data sources, including SQL databases, Excel spreadsheets, and cloud-based applications. Power BI : Provides dynamic dashboards and reporting tools.

Power BI 52

Power BI Analytics Analytics Machine Learning 52

IBM Journey to AI blog

JULY 3, 2024

To power AI and analytics workloads across your transactional and purpose-built databases, you must ensure they can seamlessly integrate with an open data lakehouse architecture without duplication or additional extract, transform, load (ETL) processes.

AI 45

AI AI Data Quality Database 45

Pickl AI

AUGUST 9, 2024

Understanding the differences between SQL and NoSQL databases is crucial for students. Understanding ETL (Extract, Transform, Load) processes is vital for students. Future Trends Exploring emerging trends in Big Data, such as the rise of edge computing, quantum computing, and advancements in artificial intelligence.

Big Data 52

Big Data Big Data Big Data Analytics Big Data Analytics 52

ODSC - Open Data Science

DECEMBER 9, 2024

Switching contexts across tools like Pandas, SciKit-Learn, SQL databases, and visualization engines creates cognitive burden. Were talking automated data cleaning, ETL pipeline generation, feature selection for models, hyperparameter tuningremoving grunt work to free up analyst time/energy for higher thinking.

Data Science 40

Data Science Machine Learning Machine Learning Python 40

phData

JULY 18, 2023

This typically results in long-running ETL pipelines that cause decisions to be made on stale or old data. Business-Focused Operation Model: Teams can shed countless hours of managing long-running and complex ETL pipelines that do not scale. This enables an automated continuous integration/continuous deployment system (CI/CD).

Data Warehouse 52

Data Warehouse Analytics Analytics SQL 52

IBM Journey to AI blog

OCTOBER 30, 2024

How the watsonx Regulatory Compliance Platform accelerates risk management The watsonx.ai™, watsonx.gov, and watsonx.data™ components of the platform are advanced artificial intelligence (AI) modules that offer a wide range of advance technical features designed to meet the unique needs of the industry.

Machine Learning 95

Machine Learning Machine Learning ETL AI 95

AWS Machine Learning Blog

FEBRUARY 18, 2025

The assistant is connected to internal and external systems, with the capability to query various sources such as SQL databases, Amazon CloudWatch logs, and third-party tools to check the live system health status. Creating ETL pipelines to transform log data Preparing your data to provide quality results is the first step in an AI project.

AWS 71

AWS Database ETL AI 71