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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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.

Data Engineering 52

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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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SQL AWS Database Business Intelligence 75

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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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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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.

Data Governance 52

Data Governance Tableau Hadoop Data Pipeline 52

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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Business Intelligence Business Intelligence SQL Data Visualization 52

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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Data Engineering Data Engineer Data Engineering Data Engineering 52

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?

Data Quality 52

Data Quality Data Lakes Data Warehouse Big Data 52

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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Data Warehouse Business Intelligence Business Intelligence Database 52

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.

Machine Learning 52

Machine Learning Machine Learning Python Data Scientist 52

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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SQL Data Lakes Data Analyst AWS 128

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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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

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!

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SQL Data Engineering Data Engineering Data Engineering 253

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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Data Quality Data Profiling Data Governance Machine Learning 74

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.

Data Governance 52

Data Governance Tableau Analytics Analytics 52

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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Data Lakes AI AI Data Governance 73

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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IBM Journey to AI blog

DECEMBER 16, 2022

It seamlessly integrates with IBM’s data integration, data observability, and data virtualization products as well as with other IBM technologies that analysts and data scientists use to create business intelligence reports, conduct analyses and build AI models. Everybody wins with a data catalog.

Data Quality 52

Data Quality Data Governance Data Wrangling Data Scientist 52

phData

DECEMBER 12, 2023

This blog was written by Sara Price and edited by Sunny Yan. In this blog, we’ll demonstrate how to utilize data to drive successful targeted and personalized campaigns for your fanbase to increase revenue, boost operational efficiency, and improve cross-departmental collaboration—all while providing an enriched fan experience.

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Data Warehouse Machine Learning Machine Learning Tableau 52

AWS Machine Learning Blog

APRIL 12, 2023

From now on, we will launch a retraining every 3 months and, as soon as possible, will use up to 1 year of data to account for the environmental condition seasonality. When deploying this system on other assets, we will be able to reuse this automated process and use the initial training to validate our sensor data pipeline.

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Pickl AI

FEBRUARY 8, 2023

Data Scientists and Data Analysts have been using ChatGPT for Data Science to generate codes and answers rapidly. In the following blog, let’s look at how ChatGPT changes human function. The entire process involves cleaning, Merging and changing the data format. This data can help in building the project pipeline.

Data Science 52

Data Science Data Scientist Machine Learning Machine Learning 52

IBM Journey to AI blog

JULY 1, 2024

Whenever anyone talks about data lineage and how to achieve it, the spotlight tends to shine on automation. This is expected, as automating the process of calculating and establishing lineage is crucial to understanding and maintaining a trustworthy system of data pipelines. This made things simple.

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phData

SEPTEMBER 25, 2024

Under this category, tools with pre-built connectors for popular data sources and visual tools for data transformation are better choices. This setting ensures that the data pipeline adapts to changes in the Source schema according to user-specific needs. Another way is to add the Snowflake details through Fivetran.

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Alation

APRIL 14, 2022

Data pipeline orchestration. Moving/integrating data in the cloud/data exploration and quality assessment. There are four critical components needed for a successful migration: AI/ML models to automate the discovery and semantics of the data. On-premises business intelligence and databases.

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Data Governance ML ML Cloud Data 59