Dataconomy

JUNE 18, 2025

Extract, Transform, Load (ETL) The ETL process involves extracting data from various sources, transforming it into a suitable format, and loading it into data warehouses, typically utilizing batch processing. Types of data integration methods There are several methods used for data integration, each suited for different scenarios.

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Dataconomy

JUNE 16, 2025

In contrast, unstructured data, such as text documents or images, lacks this formal structure, while semi-structured data sits somewhere in between, containing both organized elements and free-form content. Each piece of information is stored in a specific place, making it highly searchable and manageable.

Database 91

Database Data Lakes ETL SQL 91

databricks

JUNE 4, 2025

Events Data + AI Summit Data + AI World Tour Data Intelligence Days Event Calendar Blog and Podcasts Databricks Blog Explore news, product announcements, and more Databricks Mosaic Research Blog Discover the latest in our Gen AI research Data Brew Podcast Let’s talk data!

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Pickl AI

APRIL 9, 2025

Summary: This guide explores the top list of ETL tools, highlighting their features and use cases. It provides insights into considerations for choosing the right tool, ensuring businesses can optimize their data integration processes for better analytics and decision-making. What is ETL? What are ETL Tools?

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Pickl AI

JANUARY 28, 2025

Summary: Understanding Business Intelligence Architecture is essential for organizations seeking to harness data effectively. By implementing a robust BI architecture, businesses can make informed decisions, optimize operations, and gain a competitive edge in their industries. What is Business Intelligence Architecture?

Business Intelligence 52

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Smart Data Collective

AUGUST 17, 2022

Kafka And ETL Processing: You might be using Apache Kafka for high-performance data pipelines, stream various analytics data, or run company critical assets using Kafka, but did you know that you can also use Kafka clusters to move data between multiple systems. A three-step ETL framework job should do the trick. Conclusion.

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Dataconomy

SEPTEMBER 4, 2023

Data models help visualize and organize data, processing applications handle large datasets efficiently, and analytics models aid in understanding complex data sets, laying the foundation for business intelligence. Use ETL (Extract, Transform, Load) processes or data integration tools to streamline data ingestion.

Analytics 203

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AWS Machine Learning Blog

OCTOBER 9, 2024

To learn more, see the documentation. To learn more, see the documentation. Using Amazon QuickSight for anomaly detection Amazon QuickSight is a fast, cloud-powered, business intelligence service that delivers insights to everyone in the organization. To learn more, see the documentation.

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Pickl AI

JULY 3, 2023

What is Business Intelligence? Business Intelligence (BI) refers to the technology, techniques, and practises that are used to gather, evaluate, and present information about an organisation in order to assist decision-making and generate effective administrative action. billion in 2015 and reached around $26.50

Business Intelligence 52

Business Intelligence Business Intelligence SQL Data Visualization 52

Smart Data Collective

APRIL 29, 2020

Extraction, Transform, Load (ETL). The extraction of raw data, transforming to a suitable format for business needs, and loading into a data warehouse. Dataform enables the creation of a central repository for defining data throughout an organisation, as well as discovering datasets and documenting data in a catalogue.

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Pickl AI

OCTOBER 10, 2024

Inconsistent or unstructured data can lead to faulty insights, so transformation helps standardise data, ensuring it aligns with the requirements of Analytics, Machine Learning , or Business Intelligence tools. AWS Glue AWS Glue is a fully managed ETL service provided by Amazon Web Services.

Data Quality 52

Data Quality AWS Machine Learning Machine Learning 52

Pickl AI

MARCH 19, 2025

MongoDB MongoDB is a NoSQL database that stores data in flexible, JSON-like documents. It is commonly used for analytics and business intelligence, helping organisations make data-driven decisions. It allows businesses to store and analyse large datasets without worrying about infrastructure management.

Data Engineering 52

Data Engineering Data Engineering Data Engineer Data Engineering 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. Examples of reverse ETL tools include Weld or Census, or Hightouch.

Data Warehouse 52

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Precisely

APRIL 3, 2023

The Long Road from Batch to Real-Time Traditional “extract, transform, load” (ETL) systems were built under certain constraints, stemming from the cost of technology and implementation resources, as well as the inherent limits of computational power. Today’s world calls for a streaming-first approach.

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Pickl AI

AUGUST 9, 2024

Introduction Dimensional modelling is a design approach used in data warehousing and business intelligence that structures data into a format that is intuitive and efficient for querying and reporting. This documentation is invaluable for future reference and modifications.

Data Warehouse 52

Data Warehouse Data Quality ETL Business Intelligence 52

AWS Machine Learning Blog

JUNE 25, 2024

To create and share customer feedback analysis without the need to manage underlying infrastructure, Amazon QuickSight provides a straightforward way to build visualizations, perform one-time analysis, and quickly gain business insights from customer feedback, anytime and on any device.

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Alation

MAY 24, 2022

The Lineage & Dataflow API is a good example enabling customers to add ETL transformation logic to the lineage graph. This kit offers an open DQ API, developer documentation, onboarding, integration best practices, and co-marketing support. A pillar of Alation’s platform strategy is openness and extensibility.

Data Quality 98

Data Quality Data Governance ETL Data Observability 98

phData

MAY 11, 2023

In Matillion ETL, the Git integration enables an organization to connect to any Git offering (e.g., For Matillion ETL, the Git integration requires a stronger understanding of the workflows and systems to effectively manage a larger team. This is a key component of the “Data Productivity Cloud” and closing the ETL gap with Matillion.

ETL 52

ETL Analytics Analytics Data Models 52

Alation

FEBRUARY 7, 2023

Data warehouses obfuscate data’s origin In 2013, I was a Business Intelligence Engineer at a financial services company. The business analysts were dealing with a problem that may sound familiar to folks in the data management space. They sought documentation to help them locate the source of the data from the warehouse.

Data Warehouse 52

Data Warehouse ETL Business Intelligence Business Intelligence 52

Pickl AI

AUGUST 11, 2024

Document and Communicate Maintain thorough documentation of fact table designs, including definitions, calculations, and relationships. ETL Tools Informatica, Talend, and Apache Airflow enable the extraction of data from source systems, transformation into the desired format, and loading into the dimensional model.

Data Quality 52

Data Quality Data Warehouse Data Governance Analytics 52

phData

AUGUST 10, 2023

In data vault implementations, critical components encompass the storage layer, ELT technology, integration platforms, data observability tools, Business Intelligence and Analytics tools, Data Governance , and Metadata Management solutions. This is where automation tools come into play. Leading to significant productivity gains.

SQL 52

SQL Data Observability Data Quality Data Pipeline 52

databricks

JUNE 12, 2025

Events Data + AI Summit Data + AI World Tour Data Intelligence Days Event Calendar Blog and Podcasts Databricks Blog Explore news, product announcements, and more Databricks Mosaic Research Blog Discover the latest in our Gen AI research Data Brew Podcast Let’s talk data!

SQL 248

SQL Data Engineering Data Engineer Data Engineering 248

IBM Journey to AI blog

JULY 3, 2024

These include time series, documentation, messaging, key-value, full-text search and in-memory databases, which meet various needs, such as IoT, content management and geospatial applications. With the right data, you can create a data-driven organization that drives business value and innovation.

AI 45

AI Data Quality AI Database 45

DagsHub

NOVEMBER 11, 2024

Textual Data Textual data is one of the most common forms of unstructured data and can be in the format of documents, social media posts, emails, web pages, customer reviews, or conversation logs. These capture the semantic relationships between words, facilitating tasks like classification and clustering within ETL pipelines.

AI 52

AI AI Data Lakes Database 52

IBM Journey to AI blog

JULY 17, 2023

These encoder-only architecture models are fast and effective for many enterprise NLP tasks, such as classifying customer feedback and extracting information from large documents. ” Vitaly Tsivin, EVP Business Intelligence at AMC Networks. These Slate models are fine-tuned via Jupyter notebooks and APIs.

AI 74

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ODSC - Open Data Science

SEPTEMBER 29, 2023

Organizations that can capture, store, format, and analyze data and apply the business intelligence gained through that analysis to their products or services can enjoy significant competitive advantages. Spark is more focused on data science, ingestion, and ETL, while HPCC Systems focuses on ETL and data delivery and governance.

Data Lakes 52

Data Lakes Clustering Big Data Big Data 52

phData

SEPTEMBER 19, 2023

Metadata Management can be performed manually by creating spreadsheets and documents notating information about the various datasets. By incorporating metadata into the data model, users can easily discover, understand, and interpret the data stored in the lake.

Data Lakes 52

Data Lakes Data Models Data Modeling Data Warehouse 52

phData

OCTOBER 11, 2023

Microsoft Power BI is a dynamic and interactive data visualization platform primarily focusing on business intelligence. See the Power BI documentation. Data Processing Within KNIME’s toolkit, you’ll find an extensive array of nodes catering to data extraction, transformation, and loading (ETL).

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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.

Data Warehouse 52

Data Warehouse Analytics Analytics Cloud Data 52

databricks

JUNE 16, 2025

Events Data + AI Summit Data + AI World Tour Data Intelligence Days Event Calendar Blog and Podcasts Databricks Blog Explore news, product announcements, and more Databricks Mosaic Research Blog Discover the latest in our Gen AI research Data Brew Podcast Let’s talk data!

Data Science 130

Data Science Artificial Intelligence Business Intelligence Business Intelligence 130

Flipboard

MAY 15, 2025

Data environments in data-driven organizations are changing to meet the growing demands for analytics , including business intelligence (BI) dashboarding, one-time querying, data science , machine learning (ML), and generative AI. catalog_name}.client.region runtime and Amazon EMR Serverless.

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AWS Machine Learning Blog

OCTOBER 11, 2024

Create business intelligence (BI) dashboards for visual representation and analysis of event data. A streamlined process should include steps to ensure that events are promptly detected, prioritized, acted upon, and documented for future reference and compliance purposes, enabling efficient operational event management at scale.

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