IBM Data Science in Practice

JANUARY 13, 2025

The blog post explains how the Internal Cloud Analytics team leveraged cloud resources like Code-Engine to improve, refine, and scale the data pipelines. Background One of the Analytics teams tasks is to load data from multiple sources and unify it into a data warehouse.

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Dataversity

MAY 26, 2023

Suppose you’re in charge of maintaining a large set of data pipelines from cloud storage or streaming data into a data warehouse. How can you ensure that your data meets expectations after every transformation? That’s where data quality testing comes in.

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Dataversity

JANUARY 25, 2023

The emergence of advanced data storage technologies, such as cloud computing, data hubs, and data lakes, makes us question the role of traditional data warehouses in modern data architecture. Data warehouses were first introduced in the […] The post Are Data Warehouses Still Relevant?

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Pickl AI

JULY 8, 2024

Summary: This blog explains how to build efficient data pipelines, detailing each step from data collection to final delivery. Introduction Data pipelines play a pivotal role in modern data architecture by seamlessly transporting and transforming raw data into valuable insights.

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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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Data Science Connect

JANUARY 27, 2023

Data engineering is a crucial field that plays a vital role in the data pipeline of any organization. It is the process of collecting, storing, managing, and analyzing large amounts of data, and data engineers are responsible for designing and implementing the systems and infrastructure that make this possible.

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IBM Journey to AI blog

OCTOBER 22, 2024

This adaptability allows organizations to align their data integration efforts with distinct operational needs, enabling them to maximize the value of their data across diverse applications and workflows. This strategy helps organizations optimize data usage, expand into new markets, and increase revenue.

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phData

MARCH 8, 2023

Fivetran, a cloud-based automated data integration platform, has emerged as a leading choice among businesses looking for an easy and cost-effective way to unify their data from various sources. Fivetran is used by businesses to centralize data from various sources into a single, comprehensive data warehouse.

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phData

JUNE 14, 2023

Ultimately, the goal of a CI/CD pipeline is to ensure the safe deployment of new changes to both Snowflake’s non-production and production environments. In this blog, we will explore the benefits of enabling the CI/CD pipeline for database platforms.

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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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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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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. Everyone can do it in a matter of minutes.

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phData

APRIL 29, 2024

In our previous blog, Top 5 Fivetran Connectors for Financial Services , we explored Fivetran’s capabilities that address the data integration needs of the finance industry. Now, let’s cover the healthcare industry, which also has a surging demand for data and analytics, along with the underlying processes to make it happen.

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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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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. What Are Matillion Jobs and Why Do They Matter?

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Alation

JANUARY 17, 2023

The modern data stack is a combination of various software tools used to collect, process, and store data on a well-integrated cloud-based data platform. It is known to have benefits in handling data due to its robustness, speed, and scalability. A typical modern data stack consists of the following: A data warehouse.

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IBM Journey to AI blog

OCTOBER 16, 2023

How to scale AL and ML with built-in governance A fit-for-purpose data store built on an open lakehouse architecture allows you to scale AI and ML while providing built-in governance tools. 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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DrivenData Labs

MAY 21, 2024

The second is to provide a directed acyclic graph (DAG) for data pipelining and model building. If you use the filesystem as an intermediate data store, you can easily DAG-ify your data cleaning, feature extraction, model training, and evaluation. Teams that primarily access hosted data or assets (e.g.,

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IBM Journey to AI blog

SEPTEMBER 19, 2023

By analyzing datasets, data scientists can better understand their potential use in an algorithm or machine learning model. The data science lifecycle Data science is iterative, meaning data scientists form hypotheses and experiment to see if a desired outcome can be achieved using available data.

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phData

FEBRUARY 3, 2023

More and more businesses are looking to better leverage their outsourced call center data to make more data-driven decisions. To do this on your own, you would need to create a data warehouse, optimize the reporting performance, and very clearly visualize the data. Another way to think of it is as Data Activation.

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Alation

APRIL 14, 2023

Practitioners and hands-on data users were thrilled to be there, and many connected as they shared their progress on their own data stack journeys. People were familiar with the value of a data catalog (and the growing need for data governance ), though many admitted to being somewhat behind on their journeys.

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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

SEPTEMBER 15, 2023

In order to unlock the potential of these tools, your CRM data must remain synced between Salesforce and Snowflake. Salesforce Sync Out offers an excellent and cost-efficient solution for seamlessly ingesting Salesforce data into Snowflake. Warehouse for loading the data (start with XSMALL or SMALL warehouses).

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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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IBM Journey to AI blog

JULY 17, 2023

In this blog, I will cover: What is watsonx.ai? sales conversation summaries, insurance coverage, meeting transcripts, contract information) Generate: Generate text content for a specific purpose, such as marketing campaigns, job descriptions, blogs or articles, and email drafting support. What capabilities are included in watsonx.ai?

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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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phData

NOVEMBER 2, 2023

Managing data pipelines efficiently is paramount for any organization. The Snowflake Data Cloud has introduced a groundbreaking feature that promises to simplify and supercharge this process: Snowflake Dynamic Tables. What are Snowflake Dynamic Tables?

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Iguazio

JANUARY 22, 2024

But doing so requires significant engineering, quality data and overcoming risks. In this blog post, we show all the elements and practices you need to to take to productize LLMs and generative AI. You can watch the full talk this blog post is based on, which took place at ODSC West 2023, here. This helps cleanse the data.

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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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phData

FEBRUARY 14, 2023

Data integration is essentially the Extract and Load portion of the Extract, Load, and Transform (ELT) process. Data ingestion involves connecting your data sources, including databases, flat files, streaming data, etc, to your data warehouse. Snowflake provides native ways for data ingestion.

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Pickl AI

JUNE 7, 2024

At the heart of this process lie ETL Tools—Extract, Transform, Load—a trio that extracts data, tweaks it, and loads it into a destination. Choosing the right ETL tool is crucial for smooth data management. This blog will delve into ETL Tools, exploring the top contenders and their roles in modern data integration.

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phData

OCTOBER 12, 2023

This blog was co-written by Sam Hall and Dakota Kelley In our previous blog , we discussed some ways Fivetran and dbt solve ELT for enterprise data consumption and analytics. As your data organization grows, the scalability of your data platform matters. These allow you to scale your pipelines quickly.

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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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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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phData

SEPTEMBER 5, 2023

Let’s briefly look at the key components and their roles in this process: Azure Data Factory (ADF) : ADF will serve as our data orchestration and integration platform. 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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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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AWS Machine Learning Blog

NOVEMBER 1, 2023

Jeff Newburn is a Senior Software Engineering Manager leading the Data Engineering team at Logikcull – A Reveal Technology. He oversees the company’s data initiatives, including data warehouses, visualizations, analytics, and machine learning.

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