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.

AI 103

AI AI Data Governance Data Pipeline 103

ODSC - Open Data Science

MARCH 19, 2025

As AI and data engineering continue to evolve at an unprecedented pace, the challenge isnt just building advanced modelsits integrating them efficiently, securely, and at scale. Walk away with practical strategies to bridge the gap between unstructured data and AI applications, improving model performance and decision-making.

Data Engineering 52

Data Engineering Data Engineering Data Engineering Data Engineer 52

ODSC - Open Data Science

FEBRUARY 24, 2023

Cleanlab GitHub | Website Cleanlab is focused on data-centric AI (DCAI), providing algorithms/interfaces to help companies (across all industries) improve the quality of their datasets and diagnose/fix various issues in them. You can even connect directly to 20+ data sources to work with data within minutes.

Exploratory Data Analysis 126

Exploratory Data Analysis Data Visualization Data Analysis Data Analysis 126

IBM Journey to AI blog

OCTOBER 12, 2023

But the implementation of AI is only one piece of the puzzle. The tasks behind efficient, responsible AI lifecycle management The continuous application of AI and the ability to benefit from its ongoing use require the persistent management of a dynamic and intricate AI lifecycle—and doing so efficiently and responsibly.

AI 93

AI AI Data Scientist Data Governance 93

Dataconomy

MARCH 19, 2025

Roles within a data science team Data engineer: Responsible for building and managing data pipelines. Data visualization developer: Creates interactive dashboards for data analysis. Data architect: Designs robust data management systems for efficient data processing.

Data Science 91

Data Science Citizen Data Scientist Data Scientist Machine Learning 91

Tableau

MAY 19, 2021

Fortunately, a modern data stack (MDS) using Fivetran, Snowflake, and Tableau makes it easier to pull data from new and various systems, combine it into a single source of truth, and derive fast, actionable insights. What is a modern data stack?

Tableau 91

Tableau Cloud Data Data Pipeline Analytics 91

IBM Journey to AI blog

OCTOBER 16, 2023

Artificial intelligence (AI) adoption is still in its early stages. As more businesses use AI systems and the technology continues to mature and change, improper use could expose a company to significant financial, operational, regulatory and reputational risks. ” Are foundation models trustworthy?

AI 88

AI AI Data Warehouse ML 88

AWS Machine Learning Blog

AUGUST 12, 2024

Instead, organizations are increasingly looking to take advantage of transformative technologies like machine learning (ML) and artificial intelligence (AI) to deliver innovative products, improve outcomes, and gain operational efficiencies at scale.

ML 121

ML ML AWS AI 121

Smart Data Collective

SEPTEMBER 19, 2022

Businesses in the Fintech industry can harness the power of big data to personalize chatbot customer service. AI-powered chatbots will access raw data, allowing them to answer customer questions accurately and straight to the point. ETL and Business Intelligence solutions make dealing with large volumes of data easy.

Big Data 145

Big Data Big Data Big Data Analytics Big Data Analytics 145

IBM Journey to AI blog

SEPTEMBER 19, 2023

Overview: Data science vs data analytics Think of data science as the overarching umbrella that covers a wide range of tasks performed to find patterns in large datasets, structure data for use, train machine learning models and develop artificial intelligence (AI) applications.

Data Science 94

Data Science Analytics Analytics Data Scientist 94

Tableau

DECEMBER 7, 2022

Every company today is being asked to do more with less, and leaders need access to fresh, trusted KPIs and data-driven insights to manage their businesses, keep ahead of the competition, and provide unparalleled customer experiences. . But good data—and actionable insights—are hard to get. Bring your own AI with AWS.

Tableau 98

Tableau Data Warehouse Data Pipeline Data Visualization 98

Tableau

DECEMBER 7, 2022

Every company today is being asked to do more with less, and leaders need access to fresh, trusted KPIs and data-driven insights to manage their businesses, keep ahead of the competition, and provide unparalleled customer experiences. . But good data—and actionable insights—are hard to get. Bring your own AI with AWS.

Tableau 98

Tableau Data Warehouse Data Pipeline Data Visualization 98

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

phData

FEBRUARY 25, 2025

Over the years, businesses have increasingly turned to Snowflake AI Data Cloud for various use cases beyond just data analytics and business intelligence. Furthermore, Datavolo provides a graphical UI that simplifies defining data pipelines.

Data Pipeline 52

Data Pipeline ETL Data Engineering Data Engineering 52

IBM Journey to AI blog

AUGUST 4, 2023

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. 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.

Data Lakes 73

Data Lakes AI AI Data Governance 73

ODSC - Open Data Science

FEBRUARY 6, 2024

Apache Kafka For data engineers dealing with real-time data, Apache Kafka is a game-changer. This open-source streaming platform enables the handling of high-throughput data feeds, ensuring that data pipelines are efficient, reliable, and capable of handling massive volumes of data in real-time.

Data Engineering 52

Data Engineering Data Engineering Data Engineering Data Engineer 52

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. ” Romain Gaborit, CTO, Eviden, an ATOS business “We’re looking at the potential usage of Large Language Models. .

AI 74

AI AI Machine Learning Machine Learning 74

AWS Machine Learning Blog

AUGUST 8, 2024

Across 180 countries, millions of developers and hundreds of thousands of businesses use Twilio to create personalized experiences for their customers. As one of the largest AWS customers, Twilio engages with data, artificial intelligence (AI), and machine learning (ML) services to run their daily workloads.

SQL 125

SQL Data Lakes Data Analyst AWS 125

ODSC - Open Data Science

JANUARY 30, 2024

Data engineering is a hot topic in the AI industry right now. And as data’s complexity and volume grow, its importance across industries will only become more noticeable. But what exactly do data engineers do? So let’s do a quick overview of the job of data engineer, and maybe you might find a new interest.

Data Engineering 52

Data Engineering Data Engineering Data Engineering Data Engineer 52

Tableau

JUNE 8, 2021

Domain experts, for example, feel they are still overly reliant on core IT to access the data assets they need to make effective business decisions. In all of these conversations there is a sense of inertia: Data warehouses and data lakes feel cumbersome and data pipelines just aren't agile enough.

Tableau 102

Tableau Data Lakes Data Warehouse SQL 102

ODSC - Open Data Science

MAY 10, 2023

Unfortunately, even the data science industry — which should recognize tabular data’s true value — often underestimates its relevance in AI. Many mistakenly equate tabular data with business intelligence rather than AI, leading to a dismissive attitude toward its sophistication. The choice is yours.

Data Scientist 87

Data Scientist Data Science Deep Learning Deep Learning 87

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.

AI 52

AI AI Natural Language Processing Tableau 52

Tableau

MAY 19, 2021

Fortunately, a modern data stack (MDS) using Fivetran, Snowflake, and Tableau makes it easier to pull data from new and various systems, combine it into a single source of truth, and derive fast, actionable insights. What is a modern data stack?

Tableau 52

Tableau Cloud Data Data Pipeline Analytics 52

Pickl AI

AUGUST 1, 2023

The primary goal of Data Engineering is to transform raw data into a structured and usable format that can be easily accessed, analyzed, and interpreted by Data Scientists, analysts, and other stakeholders. Future of Data Engineering The Data Engineering market will expand from $18.2

Data Engineering 52

Data Engineering Data Engineering Data Engineering Data Engineer 52

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. This makes drawing actionable insights, spotting patterns, and making data-driven decisions easier.

Data Quality 52

Data Quality AWS Machine Learning Machine Learning 52

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

ODSC - Open Data Science

JANUARY 18, 2024

This individual is responsible for building and maintaining the infrastructure that stores and processes data; the kinds of data can be diverse, but most commonly it will be structured and unstructured data. They’ll also work with software engineers to ensure that the data infrastructure is scalable and reliable.

Data Engineering 52

Data Engineering Data Engineering Data Engineering Data Engineer 52

Pickl AI

APRIL 9, 2025

This stage involves optimizing the data for querying and analysis. This process ensures that organizations can consolidate disparate data sources into a unified repository for analytics and reporting, thereby enhancing business intelligence. What are ETL Tools?

ETL 52

ETL Data Warehouse AWS Business Intelligence 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 Engineering Data Engineer 248

Pickl AI

JULY 25, 2024

Data Warehouse: Its significance and relevance in the data world. Exploring Differences: Database vs Data Warehouse. Role in Data Warehousing and Business Intelligence Dimensional modelling plays a crucial role in data warehousing and business intelligence by structuring data to enhance performance and usability.

Data Warehouse 52

Data Warehouse Business Intelligence Business Intelligence Database 52

Tableau

DECEMBER 7, 2022

Every company today is being asked to do more with less, and leaders need access to fresh, trusted KPIs and data-driven insights to manage their businesses, keep ahead of the competition, and provide unparalleled customer experiences. But good data—and actionable insights—are hard to get. Let’s get into the nuts and bolts.

Tableau 55

Tableau Data Warehouse Data Pipeline Data Visualization 55

Women in Big Data

NOVEMBER 27, 2024

By maintaining historical data from disparate locations, a data warehouse creates a foundation for trend analysis and strategic decision-making. How to Choose a Data Warehouse for Your Big Data Choosing a data warehouse for big data storage necessitates a thorough assessment of your unique requirements.

Data Warehouse 59

Data Warehouse Big Data Big Data Azure 59

IBM Journey to AI blog

DECEMBER 16, 2022

Gartner calls out IBM’s innovation in metadata and AI-/ML-driven automation in Watson Knowledge Catalog on Cloud Pak for Data, along with fully integrated quality and governance capabilities, as key differentiators that make IBM a leading vendor in competitive evaluations. Everybody wins with a data catalog.

Data Quality 52

Data Quality Data Governance Data Wrangling Data Scientist 52

Pickl AI

FEBRUARY 8, 2023

Data Scientists and Data Analysts have been using ChatGPT for Data Science to generate codes and answers rapidly. Data Manipulation The process through which you can change the data according to your project requirement for further data analysis is known as Data Manipulation.

Data Science 52

Data Science Data Scientist Machine Learning Machine Learning 52

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.

Data Quality 74

Data Quality Data Profiling Data Governance Analytics 74

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.

AWS 108

AWS ML ML Machine Learning 108

Tableau

JUNE 8, 2021

Domain experts, for example, feel they are still overly reliant on core IT to access the data assets they need to make effective business decisions. In all of these conversations there is a sense of inertia: Data warehouses and data lakes feel cumbersome and data pipelines just aren't agile enough.

Tableau 52

Tableau Data Lakes Data Warehouse SQL 52