IBM Journey to AI blog

JULY 30, 2024

As a result of this, your gen AI initiatives are built on a solid foundation of trusted, governed data. Bring in data engineers to assess data quality and set up data preparation processes This is when your data engineers use their expertise to evaluate data quality and establish robust data preparation processes.

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Marktechpost

JUNE 5, 2024

In addition, organizations that rely on data must prioritize data quality review. Data profiling is a crucial tool. For evaluating data quality. Data profiling gives your company the tools to spot patterns, anticipate consumer actions, and create a solid data governance plan.

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Pickl AI

APRIL 14, 2023

Falling into the wrong hands can lead to the illicit use of this data. Hence, adopting a Data Platform that assures complete data security and governance for an organization becomes paramount. In this blog, we are going to discuss more on What are Data platforms & Data Governance.

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Pickl AI

DECEMBER 4, 2023

In the realm of Data Intelligence, the blog demystifies its significance, components, and distinctions from Data Information, Artificial Intelligence, and Data Analysis. Data Intelligence emerges as the indispensable force steering businesses towards informed and strategic decision-making. These insights?

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IBM Journey to AI blog

JULY 3, 2024

Your data strategy should incorporate databases designed with open and integrated components, allowing for seamless unification and access to data for advanced analytics and AI applications within a data platform. This enables your organization to extract valuable insights and drive informed decision-making.

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IBM Journey to AI blog

OCTOBER 14, 2024

In almost all cases, the data needs to be classified, filtered and governed in the context of the lifecycle of the use case. Donahue: At the enterprise or company level, “good” data is clean, structured and enriched. You may ask, “What does that have to do with unstructured data?”

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Flipboard

MARCH 22, 2023

In this post, we show how to configure a new OAuth-based authentication feature for using Snowflake in Amazon SageMaker Data Wrangler. Snowflake is a cloud data platform that provides data solutions for data warehousing to data science. Specify session:role-any as the new scope.

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IDP Data Scientist Categorization Data Quality 123

TheSequence

JULY 5, 2023

Like any large tech company, data is the backbone of the Uber platform. Not surprisingly, data quality and drifting is incredibly important. Many data drift error translates into poor performance of ML models which are not detected until the models have ran.

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AWS Machine Learning Blog

NOVEMBER 15, 2023

Content redaction: Each customer audio interaction is recorded as a stereo WAV file, but could potentially include sensitive information such as HIPAA-protected and personally identifiable information (PII). Scalability: This architecture needed to immediately scale to thousands of calls per day and millions of calls per year.

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TransOrg Analytics

AUGUST 9, 2024

Eight prominent concepts stand out: Customer Data Platforms (CDPs), Master Data Management (MDM), Data Lakes, Data Warehouses, Data Lakehouses, Data Marts, Feature Stores, and Enterprise Resource Planning (ERP). Pros: Data Consistency: Ensures consistent and accurate data across the organization.

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Machine Learning ETL Big Data Data Quality 52

Pickl AI

OCTOBER 10, 2024

Summary: Data transformation tools streamline data processing by automating the conversion of raw data into usable formats. These tools enhance efficiency, improve data quality, and support Advanced Analytics like Machine Learning. The right tool can significantly enhance efficiency, scalability, and data quality.

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Pickl AI

OCTOBER 6, 2024

Understanding these methods helps organizations optimize their data workflows for better decision-making. Introduction In today’s data-driven world, efficient data processing is crucial for informed decision-making and business growth. This phase is crucial for enhancing data quality and preparing it for analysis.

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Pickl AI

JUNE 23, 2023

At the same time, it emphasizes the collection, storage, and processing of high-quality data to drive accurate and reliable AI models. Thus, by adopting a data-centric approach, organizations can unlock the true potential of their data and gain valuable insights that lead to informed decision-making.

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AWS Machine Learning Blog

AUGUST 4, 2023

The real-time inference call data is first passed to the SageMaker Data Wrangler container in the inference pipeline, where it is preprocessed and passed to the trained model for product recommendation. For more information, refer to Creating roles and attaching policies (console). Creating the dataset may take some time.

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ODSC - Open Data Science

JULY 13, 2023

While gathering operational and consumer information can benefit businesses, they often face obstacles. Some of the top data challenges in the retail industry involve collection and application. Gathering massive amounts of information can be relatively easy, but properly utilizing it can be complex, leading to these data challenges.

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Heartbeat

DECEMBER 7, 2023

Data should have an independent team responsible for its creation, delivery, and sustainability. This team should consist of experts who know the business domain where the data comes from and should be something other than general-purpose Information and Communication Technologies (ICT) teams. What is Data Mesh?

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The MLOps Blog

MARCH 15, 2023

This is what data processing pipelines do for you. Automating myriad steps associated with pipeline data processing, helps you convert the data from its raw shape and format to a meaningful set of information that is used to drive business decisions. This ensures that the data is accurate, consistent, and reliable.

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ODSC - Open Data Science

OCTOBER 20, 2023

The Tangent Information Modeler, Time Series Modeling Reinvented Philip Wauters | Customer Success Manager and Value Engineer | Tangent Works Existing techniques for modeling time series data face limitations in scalability, agility, explainability, and accuracy.

Data Science 52

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Marktechpost

JULY 17, 2023

Information created intentionally rather than as a result of actual events is known as synthetic data. Synthetic data is generated algorithmically and used to train machine learning models, validate mathematical models, and act as a stand-in for test production or operational data test datasets.

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Machine Learning Data Scientist Computer Vision Deep Learning 52

Snorkel AI

JUNE 9, 2023

Snorkel AI wrapped the second day of our The Future of Data-Centric AI virtual conference by showcasing how Snorkel’s data-centric platform has enabled customers to succeed, taking a deep look at Snorkel Flow’s capabilities, and announcing two new solutions.

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Snorkel AI

JUNE 9, 2023

Snorkel AI wrapped the second day of our The Future of Data-Centric AI virtual conference by showcasing how Snorkel’s data-centric platform has enabled customers to succeed, taking a deep look at Snorkel Flow’s capabilities, and announcing two new solutions.

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Large Language Models Data Scientist Machine Learning Computer Vision 52

Pickl AI

APRIL 26, 2024

The blog also presents popular data analytics courses, emphasizing their curriculum, learning methods, certification opportunities, and benefits to help aspiring Data Analysts choose the proper training for their career advancement. Describe a situation where you had to think creatively to solve a data-related challenge.

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Snorkel AI

JULY 19, 2023

But this approach is expensive, time-consuming, and out of reach for all but the most well-funded companies, making the use of free, open-source alternatives for data curation appealing if sufficiently high data quality can be achieved.

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Snorkel AI

JULY 19, 2023

But this approach is expensive, time-consuming, and out of reach for all but the most well-funded companies, making the use of free, open-source alternatives for data curation appealing if sufficiently high data quality can be achieved.

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Categorization ChatGPT Large Language Models Generative AI 52

Snorkel AI

JULY 19, 2023

But this approach is expensive, time-consuming, and out of reach for all but the most well-funded companies, making the use of free, open-source alternatives for data curation appealing if sufficiently high data quality can be achieved.

Categorization 52

Categorization ChatGPT Large Language Models Generative AI 52

Snorkel AI

JULY 19, 2023

But this approach is expensive, time-consuming, and out of reach for all but the most well-funded companies, making the use of free, open-source alternatives for data curation appealing if sufficiently high data quality can be achieved.

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The MLOps Blog

AUGUST 3, 2023

Stefan is a software engineer, data scientist, and has been doing work as an ML engineer. He also ran the data platform in his previous company and is also co-creator of open-source framework, Hamilton. As you’ve been running the ML data platform team, how do you do that? Stefan: Yeah. Thanks for having me.

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ML Data Scientist Software Engineer Machine Learning 52

IBM Journey to AI blog

JULY 27, 2023

Request a demo to see how watsonx can put AI to work There’s no AI, without IA AI is only as good as the data that informs it, and the need for the right data foundation has never been greater. According to IDC, stored data is expected to grow up to 250% over the next 5 years.

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Unite.AI

JANUARY 22, 2025

We also worked on making integration easy to use for less technical data consumers – from the user interface and how people collaborate and govern data to how they build transforms and workflows. What makes data GenAI-ready, and how does Nexla address these requirements effectively? Its the same with people.

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Pickl AI

JUNE 11, 2024

Summary: A data warehouse is a central information hub that stores and organizes vast amounts of data from different sources within an organization. Unlike operational databases focused on daily tasks, data warehouses are designed for analysis, enabling historical trend exploration and informed decision-making.

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The MLOps Blog

MARCH 21, 2023

They work with other users to make sure the data reflects the business problem, the experimentation process is good enough for the business, and the results reflect what would be valuable to the business. So in building the platform, they had to focus on one or two pressing needs and build requirements around them. .

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IBM Journey to AI blog

AUGUST 4, 2023

It’s often described as a way to simply increase data access, but the transition is about far more than that. When effectively implemented, a data democracy simplifies the data stack, eliminates data gatekeepers, and makes the company’s comprehensive data platform easily accessible by different teams via a user-friendly dashboard.

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Machine Learning Metadata Automation AI 183

Flipboard

MARCH 21, 2025

Traditionally, answering this question would involve multiple data exports, complex extract, transform, and load (ETL) processes, and careful data synchronization across systems. Amazon SageMaker Catalog serves as a central repository hub to store both technical and business catalog information of the data product.

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Pickl AI

DECEMBER 25, 2024

Business Analytics involves leveraging data to uncover meaningful insights and support informed decision-making. It focuses on analyzing historical data to identify trends, patterns, and opportunities for improvement. These tools enable professionals to turn raw data into digestible insights quickly.

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