Dataversity

FEBRUARY 17, 2022

With machine learning (ML) and artificial intelligence (AI) applications becoming more business-critical, organizations are in the race to advance their AI/ML capabilities. To realize the full potential of AI/ML, having the right underlying machine learning platform is a prerequisite.

Machine Learning 52

Machine Learning Machine Learning ML ML 52

IBM Journey to AI blog

JUNE 15, 2023

There’s no debate that the volume and variety of data is exploding and that the associated costs are rising rapidly. The proliferation of data silos also inhibits the unification and enrichment of data which is essential to unlocking the new insights.

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Alation

FEBRUARY 1, 2022

About one-half of Ventana Research participants want to schedule data processes to run automatically & two-thirds seek to eliminate manual processes when working with data. Sheer volume of data makes automation with Artificial Intelligence & Machine Learning (AI & ML) an imperative.

Data Lakes 52

Data Lakes Data Governance ML ML 52

IBM Journey to AI blog

JANUARY 18, 2023

In another decade, the internet and mobile started the generate data of unforeseen volume, variety and velocity. It required a different data platform solution. Hence, Data Lake emerged, which handles unstructured and structured data with huge volume. Data fabric and data mesh as concepts have overlaps.

Data Lakes 52

Data Lakes Data Warehouse Azure Apache Hadoop 52

Precisely

JULY 18, 2024

Ensures consistent, high-quality data is readily available to foster innovation and enable you to drive competitive advantage in your markets through advanced analytics and machine learning. You must be able to continuously catalog, profile, and identify the most frequently used data. Increase metadata maturity.

Data Lakes 52

Data Lakes Data Warehouse Data Governance Machine Learning 52

phData

MAY 13, 2024

Even if organizations survive a migration to S/4 and HANA cloud, licensing and performance constraints make it difficult to perform advanced analytics on this data within the SAP environment. Most importantly, this creates options for your organization as you explore leveraging the data that has been centralized in Snowflake.

Database 52

Database Analytics Analytics Machine Learning 52

Alation

MARCH 21, 2023

While this industry has used data and analytics for a long time, many large travel organizations still struggle with data silos , which prevent them from gaining the most value from their data. What is big data in the travel and tourism industry?

Analytics 52

Analytics Analytics Data Silos Big Data 52

IBM Journey to AI blog

MARCH 14, 2024

Businesses face significant hurdles when preparing data for artificial intelligence (AI) applications. The existence of data silos and duplication, alongside apprehensions regarding data quality, presents a multifaceted environment for organizations to manage.

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The MLOps Blog

MAY 17, 2023

Often the Data Team, comprising Data and ML Engineers , needs to build this infrastructure, and this experience can be painful. 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. fillna( iris_transform_df[cols].mean())

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ETL Data Pipeline ML ML 59

IBM Journey to AI blog

FEBRUARY 2, 2023

In today’s world, data warehouses are a critical component of any organization’s technology ecosystem. They provide the backbone for a range of use cases such as business intelligence (BI) reporting, dashboarding, and machine-learning (ML)-based predictive analytics, that enable faster decision making and insights.

Data Warehouse 58

Data Warehouse Cloud Data Analytics Analytics 58

Alation

APRIL 7, 2021

It automatically surfaces clues in the data to remove the manual effort of discovery within the huge volume, variety, and veracity of data produced by the modern enterprise. Alation’s data intelligence comes from user behavior. For example, many enterprises find that data workers only use 5 to 10% of all data.

Data Governance 52

Data Governance AWS Data Silos Data Lakes 52

Pickl AI

DECEMBER 11, 2024

Efficiency emphasises streamlined processes to reduce redundancies and waste, maximising value from every data point. Common Challenges with Traditional Data Management Traditional data management systems often grapple with data silos, which isolate critical information across departments, hindering collaboration and transparency.

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Data Silos Data Pipeline Artificial Intelligence Artificial Intelligence 52

Alation

JANUARY 27, 2022

What Are the Top Data Challenges to Analytics? The proliferation of data sources means there is an increase in data volume that must be analyzed. Large volumes of data have led to the development of data lakes , data warehouses, and data management systems.

Data Governance 52

Data Governance Analytics Analytics Data Quality 52

Dataversity

APRIL 1, 2021

Click here to learn more about Amit Levi. In the data-driven world we live in today, the field of analytics has become increasingly important to remain competitive in business.

Analytics 69

Analytics Analytics Data Silos Data Lakes 69

Flipboard

DECEMBER 4, 2024

The use of separate data warehouses and lakes has created data silos, leading to problems such as lack of interoperability, duplicate governance efforts, complex architectures, and slower time to value. You can use Amazon SageMaker Lakehouse to achieve unified access to data in both data warehouses and data lakes.

Data Lakes 138

Data Lakes Data Warehouse AWS Database 138

phData

SEPTEMBER 27, 2024

Looking to build a machine-learning model for churn prediction? The atomic data provides a perfect input, capturing the full richness of customer behavior over time. Both persistent staging and data lakes involve storing large amounts of raw data. Want the best-in-class machine learning capabilities?

Data Modeling 52

Data Modeling Data Models Apache Kafka Data Lakes 52

AWS Machine Learning Blog

DECEMBER 3, 2024

Although generative AI is fueling transformative innovations, enterprises may still experience sharply divided data silos when it comes to enterprise knowledge, in particular between unstructured content (such as PDFs, Word documents, and HTML pages), and structured data (real-time data and reports stored in databases or data lakes).

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AWS Machine Learning Blog

NOVEMBER 1, 2024

Amazon SageMaker enables trial developers to build and train machine learning (ML) models that reduce the likelihood of protocol amendments and inconsistencies. Decentralized clinical trials, however, often employ a singular data lake for all of an organization’s clinical trials.

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