Flipboard

NOVEMBER 24, 2023

Data scientists and ML engineers require capable tooling and sufficient compute for their work. To pave the way for the growth of AI, BMW Group needed to make a leap regarding scalability and elasticity while reducing operational overhead, software licensing, and hardware management.

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IBM Journey to AI blog

JUNE 15, 2023

Moreover, increased regulatory requirements make it harder for enterprises to democratize data access and scale the adoption of analytics and artificial intelligence (AI). Against this challenging backdrop, the sense of urgency has never been higher for businesses to leverage AI for competitive advantage.

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Data Warehouse Data Lakes Cloud Data Analytics 110

IBM Journey to AI blog

MAY 9, 2023

Today is a revolutionary moment for Artificial Intelligence (AI). Suddenly, everybody is talking about generative AI: sometimes with excitement, other times with anxiety. The answer is that generative AI leverages recent advances in foundation models. AI is already driving results for business.

AI 110

AI AI Data Warehouse Machine Learning 110

Dataconomy

SEPTEMBER 4, 2023

Cloud-based business intelligence (BI): Cloud-based BI tools enable organizations to access and analyze data from cloud-based sources and on-premises databases. These tools offer the flexibility of accessing insights from anywhere, and they often integrate with other cloud analytics solutions.

Analytics 203

Analytics Analytics Big Data Analytics Big Data Analytics 203

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

phData

NOVEMBER 1, 2024

Get the Trendbook What is the Impact of Data Governance on GenAI? Data governance plays a critical role in the successful implementation of Generative AI (GenAI) and large language models (LLM), with 86.7% (You can read the full guide without giving us your email — keep scrolling! )

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Data Governance Data Quality ML ML 52

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.

AI 74

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AWS Machine Learning Blog

NOVEMBER 27, 2023

This post is co-authored by Daryl Martis, Director of Product, Salesforce Einstein AI. This is the third post in a series discussing the integration of Salesforce Data Cloud and Amazon SageMaker. Einstein Studio is a gateway to AI tools on Salesforce Data Cloud. Build and train models in SageMaker Canvas.

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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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Alation

JULY 18, 2022

Are your data users overwhelmed by silos and frustrated by untrusted data? Tell them to grab a catalog … and go jump in a lake. That was the message — delivered a little more elegantly than that — at Databricks’ Data+AI Summit 2022. Automatically tracking data lineage across queries executed in any language.

AI 52

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AWS Machine Learning Blog

SEPTEMBER 5, 2023

We have over 50 TB of historical equipment data and expect this data to grow quickly as more HVAC units are connected to the cloud. Data processing and model inference need to scale as our data grows. We partnered with the AI/ML experts at the Amazon ML Solutions Lab for a 14-week development effort.

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AWS Machine Learning Blog

AUGUST 4, 2023

This post is co-authored by Daryl Martis, Director of Product, Salesforce Einstein AI. This is the second post in a series discussing the integration of Salesforce Data Cloud and Amazon SageMaker. For instructions, refer to Bring Your Own AI Models to Salesforce with Einstein Studio. Follow him on [link].

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ML ML AWS AI 97

ODSC - Open Data Science

JULY 11, 2023

1] The typical application familiar to readers is much more recent, when AI operates as chatbots, enhancing or at least facilitating the user experience on many websites. Recently, however, conversational AI has taken a giant leap forward. Why Use AI to Learn About Data Centers and How Does It Work?

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Alation

APRIL 19, 2022

Data modernization is the process of transferring data to modern cloud-based databases from outdated or siloed legacy databases, including structured and unstructured data. In that sense, data modernization is synonymous with cloud migration. 5 Benefits of Data Modernization. Advanced Tooling.

Data Governance 52

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Precisely

JANUARY 25, 2024

These systems support containerized applications, virtualization, AI and machine learning, API and cloud connectivity, and more. In light of this, modernization should not be viewed as a replacement strategy so much as an approach to unifying mainframe operations with today’s cloud platforms. Best Practice 2.

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Dataversity

FEBRUARY 15, 2021

Artificial intelligence (AI) is no longer a “nice-to-have.” From business processes and smart home technology to healthcare and life sciences, AI continues to evolve and grow as it plays an increasing role in many aspects of our work, home lives, and beyond. As we bid 2020 a […].

Machine Learning 59

Machine Learning Machine Learning Artificial Intelligence Artificial Intelligence 59

Alation

APRIL 14, 2022

Data discovery is also critical for data governance , which, when ineffective, can actually hinder organizational growth. And, as organizations progress and grow, “data drift” starts to impact data usage, models, and your business. The Cloud Data Migration Challenge. Data pipeline orchestration.

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Precisely

JANUARY 18, 2024

And, they’re still a key element of the infrastructure that makes private clouds possible at many organizations. Instead of performing major surgery on their critical business systems, enterprises are opting for real-time data integration built around inherently reliable and scalable change data capture (CDC) technology.

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AWS Artificial Intelligence Artificial Intelligence Cloud Computing 52

Alation

JUNE 21, 2022

Over time, we called the “thing” a data catalog , blending the Google-style, AI/ML-based relevancy with more Yahoo-style manual curation and wikis. Thus was born the data catalog. In our early days, “people” largely meant data analysts and business analysts. Data engineers want to catalog data pipelines.

DataOps 52

DataOps Data Scientist Data Quality Data Pipeline 52

phData

JUNE 11, 2025

One question that routinely keeps many of our early Snowflake AI Data Cloud clients up at night is, “Is my org utilizing Snowflake to its fullest potential?” Depending on the requirement, it is important to choose between transient and permanent tables, as well as data recovery needs and downtime considerations.

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AWS Machine Learning Blog

APRIL 12, 2023

The PdMS includes AWS services to securely manage the lifecycle of edge compute devices and BHS assets, cloud data ingestion, storage, machine learning (ML) inference models, and business logic to power proactive equipment maintenance in the cloud. This organization manages fleets of globally distributed edge gateways.

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Tableau

DECEMBER 7, 2022

As the world’s first real-time CRM, Salesforce Customer 360 and Data Cloud provide your entire organization with a single, up-to-the-minute view of your customer across any cloud. Built-in connectors bring in data from every single channel. Or, because it’s optimized for customer data, let’s call it a customer graph.)

Tableau 55

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Pickl AI

APRIL 9, 2025

This includes operations like data validation, data cleansing, data aggregation, and data normalization. The goal is to ensure that the data is consistent and ready for analysis. Loading : Storing the transformed data in a target system like a data warehouse, data lake, or even a database.

ETL 52

ETL Data Warehouse AWS Business Intelligence 52

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.

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Machine Learning Machine Learning ML ML 52

Snorkel AI

MAY 26, 2023

[link] Ahmad Khan, head of artificial intelligence and machine learning strategy at Snowflake gave a presentation entitled “Scalable SQL + Python ML Pipelines in the Cloud” about his company’s Snowpark service at Snorkel AI’s Future of Data-Centric AI virtual conference in August 2022. Welcome everybody.

SQL 52

SQL ML ML Python 52

Snorkel AI

MAY 26, 2023

[link] Ahmad Khan, head of artificial intelligence and machine learning strategy at Snowflake gave a presentation entitled “Scalable SQL + Python ML Pipelines in the Cloud” about his company’s Snowpark service at Snorkel AI’s Future of Data-Centric AI virtual conference in August 2022. Welcome everybody.

SQL 52

SQL ML ML Python 52

Dataversity

APRIL 1, 2021

In the data-driven world we live in today, the field of analytics has become increasingly important to remain competitive in business. In fact, a study by McKinsey Global Institute shows that data-driven organizations are 23 times more likely to outperform competitors in customer acquisition and nine times […].

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Analytics Analytics Data Silos Data Lakes 69

Dataversity

FEBRUARY 16, 2022

The semantic layer concept within the data stack is not new but is an increasingly popular topic of conversation. I predict that in 2022, we’ll see mainstream awareness of the semantic layer, especially as enterprises begin to see real-world examples of its benefits.

Data Lakes 52

Data Lakes Data Warehouse Cloud Data Analytics 52

Dataversity

MARCH 17, 2021

I do not think it is an exaggeration to say data analytics has come into its own over the past decade or so. What started out as an attempt to extract business insights from transactional data in the ’90s and early 2000s has now transformed into an […]. The post Is Lakehouse Architecture a Grand Unification in Data Analytics?

Analytics 52

Analytics Analytics Data Lakes Data Warehouse 52

AWS Machine Learning Blog

NOVEMBER 1, 2024

Instead, a core component of decentralized clinical trials is a secure, scalable data infrastructure with strong data analytics capabilities. Amazon Redshift is a fully managed cloud data warehouse that trial scientists can use to perform analytics.

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Data Science Blog

MARCH 14, 2023

Big Data wurde für viele Unternehmen der traditionellen Industrie zur Enttäuschung, zum falschen Versprechen. Von Data Science spricht auf Konferenzen heute kaum noch jemand und wurde hype-technisch komplett durch Machine Learning bzw. Artificial Intelligence (AI) ersetzt. Industrie 4.0). Lakehousing) und Analysemethodik (z.

Big Data 147

Big Data Big Data Apache Hadoop Data Science 147

phData

SEPTEMBER 27, 2024

Both persistent staging and data lakes involve storing large amounts of raw data. But persistent staging is typically more structured and integrated into your overall customer data pipeline. You might choose a cloud data warehouse like the Snowflake AI Data Cloud or BigQuery.

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Data Modeling Data Models Apache Kafka Data Lakes 52