AWS Machine Learning Blog

DECEMBER 4, 2024

SageMaker Unified Studio combines various AWS services, including Amazon Bedrock , Amazon SageMaker , Amazon Redshift , Amazon Glue , Amazon Athena , and Amazon Managed Workflows for Apache Airflow (MWAA) , into a comprehensive data and AI development platform. Consider a global retail site operating across multiple regions and countries.

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AWS Machine Learning Blog

OCTOBER 24, 2024

The analyst can easily pull in the data they need, use natural language to clean up and fill any missing data, and finally build and deploy a machine learning model that can accurately predict the loan status as an output, all without needing to become a machine learning expert to do so.

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AWS Machine Learning Blog

JULY 11, 2025

With users executing over 450,000 SQL queries annually against our petabyte-scale Amazon Redshift data warehouses, our business intelligence and analytics teams had become a critical bottleneck. The results: 90% faster query resolution (from hours to minutes) with zero dependency on business intelligence teams.

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AWS Machine Learning Blog

APRIL 3, 2025

Embracing generative AI with Amazon Bedrock The company has identified several use cases where generative AI can significantly impact operations, particularly in analytics and business intelligence (BI). This tool democratizes data access across the organization, enabling even nontechnical users to gain valuable insights.

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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!

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Hacker News

JULY 1, 2025

Prior to that, I spent a couple years at First Orion - a smaller data company - helping found & build out a data engineering team as one of the first engineers. We were focused on building data pipelines and models to protect our users from malicious phonecalls. Worked at IBM as a programmer too.

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Pickl AI

MARCH 19, 2025

Summary: Data engineering tools streamline data collection, storage, and processing. Learning these tools is crucial for building scalable data pipelines. offers Data Science courses covering these tools with a job guarantee for career growth. Below are 20 essential tools every data engineer should know.

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Hacker News

JULY 1, 2025

It seems like that's not the main focus of your org, but I was pleased to see a reference to RCV in your blog: [0] [0]: https://goodparty.org/blog/article/final-five-voting-explain. We empower marketers and online businesses to manage, scale, and optimize their marketing.

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Flipboard

JUNE 18, 2025

Orchestration platform Orq noted in a blog post that AI management systems include four key components: prompt management for consistent model interaction, integration tools, state management and monitoring tools to track performance. What do they need the AI application or agents to do, and how are these planned to support their work?

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Data Science Blog

FEBRUARY 4, 2023

The fusion of data in a central platform enables smooth analysis to optimize processes and increase business efficiency in the world of Industry 4.0 using methods from business intelligence , process mining and data science. Or maybe you are interested in an individual data strategy ?

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The MLOps Blog

MAY 17, 2023

We also discuss different types of ETL pipelines for ML use cases and provide real-world examples of their use to help data engineers choose the right one. What is an ETL data pipeline in ML? Xoriant It is common to use ETL data pipeline and data pipeline interchangeably.

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IBM Journey to AI blog

OCTOBER 22, 2024

Data must be combined and harmonized from multiple sources into a unified, coherent format before being used with AI models. This process is known as data integration , one of the key components to improving the usability of data for AI and other use cases, such as business intelligence (BI) and analytics.

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Smart Data Collective

SEPTEMBER 8, 2021

The data is initially extracted from a vast array of sources before transforming and converting it to a specific format based on business requirements. A lot of Open-Source ETL tools house a graphical interface for executing and designing Data Pipelines. This blog talks about the basics of ETL and ETL tools.

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IBM Journey to AI blog

APRIL 10, 2023

A well-designed data architecture should support business intelligence and analysis, automation, and AI—all of which can help organizations to quickly seize market opportunities, build customer value, drive major efficiencies, and respond to risks such as supply chain disruptions.

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AI AI Data Governance Data Pipeline 103

Alation

FEBRUARY 20, 2020

Self-service analytics tools have been democratizing data-driven decision making, but also increasing the risk of inaccurate analysis and misinterpretation. A “catalog-first” approach to business intelligence enables both empowerment and accuracy; and Alation has long enabled this combination over Tableau.

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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

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IBM Journey to AI blog

SEPTEMBER 19, 2023

Data analytics is a task that resides under the data science umbrella and is done to query, interpret and visualize datasets. Data scientists will often perform data analysis tasks to understand a dataset or evaluate outcomes.

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phData

NOVEMBER 9, 2023

This blog was originally written by Keith Smith and updated for 2024 by Justin Delisi. Snowflake’s Data Cloud has emerged as a leader in cloud data warehousing. What is a Data Lake? A Data Lake is a location to store raw data that is in any format that an organization may produce or collect.

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Alation

MARCH 31, 2022

In the breakneck world of data, which I have been privy to since the mid 1990s, business intelligence remains one of the most enduring terms. So I was surprised to learn from my colleague Myles Suer’s blog piece about Self-Service vs. Traditional BI that it was first referenced in 1865. Modern Business Intelligence.

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phData

SEPTEMBER 5, 2023

Google Analytics 4 (GA4) is a powerful tool for collecting and analyzing website and app data that many businesses rely heavily on to make informed business decisions. It enables us to create, schedule, and monitor the data pipeline, ensuring seamless movement of data between the various sources and destinations.

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IBM Journey to AI blog

OCTOBER 16, 2023

It also lets you choose the right engine for the right workload at the right cost, potentially reducing your data warehouse costs by optimizing workloads. A data store lets a business connect existing data with new data and discover new insights with real-time analytics and business intelligence.

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ODSC - Open Data Science

JANUARY 18, 2024

If you are a data scientist, you may be wondering if you can transition into data engineering. The good news is that there are many skills that data scientists already have that are transferable to data engineering. In this blog post, we will discuss how you can become a data engineer if you are a data scientist.

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IBM Journey to AI blog

OCTOBER 12, 2023

Securing AI models and their access to data While AI models need flexibility to access data across a hybrid infrastructure, they also need safeguarding from tampering (unintentional or otherwise) and, especially, protected access to data.

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IBM Journey to AI blog

JANUARY 5, 2023

The right data architecture can help your organization improve data quality because it provides the framework that determines how data is collected, transported, stored, secured, used and shared for business intelligence and data science use cases. What does a modern data architecture do for your business?

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phData

JANUARY 31, 2024

In this blog, we’ll show you how to build a robust energy price forecasting solution within the Snowflake Data Cloud ecosystem. We’ll cover how to get the data via the Snowflake Marketplace, how to apply machine learning with Snowpark , and then bring it all together to create an automated ML model to forecast energy prices.

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AWS Machine Learning Blog

AUGUST 8, 2024

RAG optimizes language model outputs by extending the models’ capabilities to specific domains or an organization’s internal data for tailored responses. This post highlights how Twilio enabled natural language-driven data exploration of business intelligence (BI) data with RAG and Amazon Bedrock.

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phData

MAY 25, 2023

How to Optimize Power BI and Snowflake for Advanced Analytics Spencer Baucke May 25, 2023 The world of business intelligence and data modernization has never been more competitive than it is today. Microsoft Power BI has been the leader in the analytics and business intelligence platforms category for several years running.

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Pickl AI

JULY 25, 2024

Introduction Dimensional modelling is crucial for organising data to enhance query performance and reporting efficiency. Effective schema design is essential for optimising data retrieval and analysis in data warehousing. Must Read Blogs: Exploring the Power of Data Warehouse Functionality.

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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. The most important reason for using DBT in Data Vault 2.0

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SQL Data Observability Data Quality Data Pipeline 52

phData

APRIL 5, 2024

With Document AI from the Snowflake Data Cloud , organizations can utilize the power of LLMs to automate the process of converting unstructured documents into organized tables with ease! In this blog, we’ll cover what the Document AI tool is, what use cases it solves, and how to integrate it with document processing pipelines.

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IBM Journey to AI blog

JULY 13, 2023

The more complete, accurate and consistent a dataset is, the more informed business intelligence and business processes become. With data observability capabilities, IBM can help organizations detect and resolve issues within data pipelines faster. appeared first on IBM Blog.

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AWS Machine Learning Blog

AUGUST 12, 2024

AWS data engineering pipeline The adaptable approach detailed in this post starts with an automated data engineering pipeline to make data stored in Splunk available to a wide range of personas, including business intelligence (BI) analysts, data scientists, and ML practitioners, through a SQL interface.

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IBM Journey to AI blog

JULY 17, 2023

IBM software products are embedding watsonx capabilities across digital labor, IT automation, security, sustainability, and application modernization to help unlock new levels of business value for clients. In this blog, I will cover: What is watsonx.ai? ” Vitaly Tsivin, EVP Business Intelligence at AMC Networks.

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Pickl AI

AUGUST 16, 2024

Summary : This blog provides a comprehensive overview of statistical tools for data-driven research. Researchers across disciplines will find valuable insights to enhance their Data Analysis skills and produce credible, impactful findings.

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Alation

FEBRUARY 20, 2020

. ; there has to be a business context, and the increasing realization of this context explains the rise of information stewardship applications.” – May 2018 Gartner Market Guide for Information Stewardship Applications. The rise of data lakes, IOT analytics, and big data pipelines has introduced a new world of fast, big data.

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IBM Journey to AI blog

AUGUST 4, 2023

Instead of handling extract, transform and load (ETL) operations within a data lake, a data mesh defines the data as a product in multiple repositories, each given its own domain for managing its data pipeline. This lets users across the organization treat the data like a product with widespread access.

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Alation

JANUARY 17, 2023

A typical modern data stack consists of the following: A data warehouse. Data ingestion/integration services. Data orchestration tools. Business intelligence (BI) platforms. These tools are used to manage big data, which is defined as data that is too large or complex to be processed by traditional means.

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