IBM Journey to AI blog

OCTOBER 22, 2024

Data is the differentiator as business leaders look to utilize their competitive edge as they implement generative AI (gen AI). Leaders feel the pressure to infuse their processes with artificial intelligence (AI) and are looking for ways to harness the insights in their data platforms to fuel this movement.

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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.

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Alation

MAY 16, 2023

But with the sheer amount of data continually increasing, how can a business make sense of it? Robust data pipelines. What is a Data Pipeline? A data pipeline is a series of processing steps that move data from its source to its destination. The answer?

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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?

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phData

JULY 17, 2023

Over the past few decades, the corporate data landscape has changed significantly. The shift from on-premise databases and spreadsheets to the modern era of cloud data warehouses and AI/ LLMs has transformed what businesses can do with data. This is where Fivetran and the Modern Data Stack come in.

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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.

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Flipboard

AUGUST 17, 2023

Amazon Redshift is the most popular cloud data warehouse that is used by tens of thousands of customers to analyze exabytes of data every day. AWS Glue is a serverless data integration service that makes it easy to discover, prepare, and combine data for analytics, ML, and application development.

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Tableau

DECEMBER 7, 2022

But good data—and actionable insights—are hard to get. Traditionally, organizations built complex data pipelines to replicate data. Those data architectures were brittle, complex, and time intensive to build and maintain, requiring data duplication and bloated data warehouse investments.

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Tableau

DECEMBER 7, 2022

But good data—and actionable insights—are hard to get. Traditionally, organizations built complex data pipelines to replicate data. Those data architectures were brittle, complex, and time intensive to build and maintain, requiring data duplication and bloated data warehouse investments.

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IBM Journey to AI blog

JULY 17, 2023

is our enterprise-ready next-generation studio for AI builders, bringing together traditional machine learning (ML) and new generative AI capabilities powered by foundation models. With watsonx.ai, businesses can effectively train, validate, tune and deploy AI models with confidence and at scale across their enterprise.

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ODSC - Open Data Science

FEBRUARY 19, 2025

In the world of AI-driven data workflows, Brij Kishore Pandey, a Principal Engineer at ADP and a respected LinkedIn influencer, is at the forefront of integrating multi-agent systems with Generative AI for ETL pipeline orchestration. Transformation : Data is cleaned, formatted, and enriched. What is an Agent?

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phData

NOVEMBER 28, 2023

In July 2023, Matillion launched their fully SaaS platform called Data Productivity Cloud, aiming to create a future-ready, everyone-ready, and AI-ready environment that companies can easily adopt and start automating their data pipelines coding, low-coding, or even no-coding at all. Or would you even go to that directly?

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ODSC - Open Data Science

AUGUST 23, 2023

Run pandas at scale on your data warehouse Most enterprise data teams store their data in a database or data warehouse, such as Snowflake, BigQuery, or DuckDB. Ponder solves this problem by translating your pandas code to SQL that can be understood by your data warehouse.

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The MLOps Blog

MARCH 15, 2023

In this post, you will learn about the 10 best data pipeline tools, their pros, cons, and pricing. A typical data pipeline involves the following steps or processes through which the data passes before being consumed by a downstream process, such as an ML model training process.

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Pickl AI

NOVEMBER 4, 2024

Effective data governance enhances quality and security throughout the data lifecycle. What is Data Engineering? Data Engineering is designing, constructing, and managing systems that enable data collection, storage, and analysis. ETL is vital for ensuring data quality and integrity. from 2025 to 2030.

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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.

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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 also get data science training on-demand wherever you are with our Ai+ Training platform.

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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.

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Pickl AI

OCTOBER 17, 2024

It highlights key components of the ETL process, best practices for efficiency, and future trends like AI integration and real-time processing, ensuring organisations can leverage their data effectively for strategic decision-making. Introduction ETL plays a crucial role in Data Management.

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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

Snorkel AI

JANUARY 24, 2023

Unfortunately accessing data across various locations and file types and then operationalizing that data for AI usage has traditionally been a painfully manual, time-consuming, and costly process. Ahmad Khan, Head of AI/ML Strategy at Snowflake, discusses the challenges of operationalizing ML in a recent talk.

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Snorkel AI

JANUARY 24, 2023

Unfortunately accessing data across various locations and file types and then operationalizing that data for AI usage has traditionally been a painfully manual, time-consuming, and costly process. Ahmad Khan, Head of AI/ML Strategy at Snowflake, discusses the challenges of operationalizing ML in a recent talk.

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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

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phData

SEPTEMBER 2, 2024

Best practices are a pivotal part of any software development, and data engineering is no exception. This ensures the data pipelines we create are robust, durable, and secure, providing the desired data to the organization effectively and consistently. Below are the best practices.

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ODSC - Open Data Science

APRIL 4, 2024

Data Analytics in the Age of AI, When to Use RAG, Examples of Data Visualization with D3 and Vega, and ODSC East Selling Out Soon Data Analytics in the Age of AI Let’s explore the multifaceted ways in which AI is revolutionizing data analytics, making it more accessible, efficient, and insightful than ever before.

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Alation

APRIL 14, 2023

the presenters elaborated on the common pain points of the cloud data warehouse today and predicted what it may look like in the future. With the rise of AI, the speakers speculated that the future modern data stack may not be designed with human consumers in mind, but set up instead for AI/ML.

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phData

DECEMBER 12, 2023

We are going to break down what we know about Victory Vicky based on all the data sources we have moved into our data warehouse. The loyalty program is located in the MarTech Stack and moves data effortlessly into the data warehouse. This information is also funneled into the data warehouse.

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Pickl AI

JULY 25, 2023

Data engineers are essential professionals responsible for designing, constructing, and maintaining an organization’s data infrastructure. They create data pipelines, ETL processes, and databases to facilitate smooth data flow and storage. Read more to know. Cloud Platforms: AWS, Azure, Google Cloud, etc.

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Pickl AI

JULY 25, 2024

Must Read Blogs: Exploring the Power of Data Warehouse Functionality. Data Lakes Vs. Data Warehouse: Its significance and relevance in the data world. Exploring Differences: Database vs Data Warehouse. It is commonly used in data warehouses for business analytics and reporting.

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DrivenData Labs

MAY 21, 2024

Hello from our new, friendly, welcoming, definitely not an AI overlord cookie logo! The second is to provide a directed acyclic graph (DAG) for data pipelining and model building. Teams that primarily access hosted data or assets (e.g., These options include DVC, Pachyderm and Quilt.

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Pickl AI

JUNE 7, 2024

Also Read: Top 10 Data Science tools for 2024. It is a process for moving and managing data from various sources to a central data warehouse. This process ensures that data is accurate, consistent, and usable for analysis and reporting. This process helps organisations manage large volumes of data efficiently.

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ODSC - Open Data Science

FEBRUARY 6, 2024

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. You can also get data science training on-demand wherever you are with our Ai+ Training platform.

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Pickl AI

OCTOBER 17, 2024

It is a data integration process that involves extracting data from various sources, transforming it into a suitable format, and loading it into a target system, typically a data warehouse. ETL is the backbone of effective data management, ensuring organisations can leverage their data for informed decision-making.

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AWS Machine Learning Blog

NOVEMBER 1, 2023

Organizations can search for PII using methods such as keyword searches, pattern matching, data loss prevention tools, machine learning (ML), metadata analysis, data classification software, optical character recognition (OCR), document fingerprinting, and encryption.

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Tableau

DECEMBER 7, 2022

But good data—and actionable insights—are hard to get. Traditionally, organizations built complex data pipelines to replicate data. Those data architectures were brittle, complex, and time intensive to build and maintain, requiring data duplication and bloated data warehouse investments.

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IBM Journey to AI blog

NOVEMBER 3, 2023

When you make it easier to work with events, other users like analysts and data engineers can start gaining real-time insights and work with datasets when it matters most. As a result, you reduce the skills barrier and increase your speed of data processing by preventing important information from getting stuck in a data warehouse.

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phData

OCTOBER 17, 2024

Using 3rd party tooling is essential if you’re a Snowflake AI Data Cloud customer. Getting your data into Snowflake, creating analytics applications from the data, and even ensuring your Snowflake account runs smoothly all require some sort of tool. The post What Free Tools Pair Well With The Snowflake AI Data Cloud?

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