Dataconomy

SEPTEMBER 4, 2023

The modern corporate world is more data-driven, and companies are always looking for new methods to make use of the vast data at their disposal. Cloud analytics is one example of a new technology that has changed the game. What is cloud analytics? How does cloud analytics work?

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ODSC - Open Data Science

AUGUST 15, 2023

Recently we’ve seen lots of posts about a variety of different file formats for data lakes. There’s Delta Lake, Hudi, Iceberg, and QBeast, to name a few. It can be tough to keep track of all these data lake formats — let alone figure out why (or if!) And I’m curious to see if you’ll agree.

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ODSC - Open Data Science

SEPTEMBER 27, 2023

In the ever-evolving world of big data, managing vast amounts of information efficiently has become a critical challenge for businesses across the globe. As data lakes gain prominence as a preferred solution for storing and processing enormous datasets, the need for effective data version control mechanisms becomes increasingly evident.

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Flipboard

OCTOBER 25, 2023

By some estimates, unstructured data can make up to 80–90% of all new enterprise data and is growing many times faster than structured data. After decades of digitizing everything in your enterprise, you may have an enormous amount of data, but with dormant value. These services write the output to a data lake.

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Dataconomy

JUNE 1, 2023

Microsoft has made good on its promise to deliver a simplified and more efficient Microsoft Fabric price model for its end-to-end platform designed for analytics and data workloads. Microsoft’s unified pricing model for the Fabric suite marks a significant advancement in the analytics and data market.

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IBM Journey to AI blog

JULY 5, 2023

Data Lakes have been around for well over a decade now, supporting the analytic operations of some of the largest world corporations. Such data volumes are not easy to move, migrate or modernize. The challenges of a monolithic data lake architecture Data lakes are, at a high level, single repositories of data at scale.

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Flipboard

DECEMBER 11, 2024

Many of these applications are complex to build because they require collaboration across teams and the integration of data, tools, and services. Data engineers use data warehouses, data lakes, and analytics tools to load, transform, clean, and aggregate data.

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Dataversity

MARCH 24, 2021

Enterprises migrating on-prem data environments to the cloud in pursuit of more robust, flexible, and integrated analytics and AI/ML capabilities are fueling a surge in cloud data lake implementations. The post How to Ensure Your New Cloud Data Lake Is Secure appeared first on DATAVERSITY.

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AWS Machine Learning Blog

DECEMBER 16, 2024

We spoke with Dr. Swami Sivasubramanian, Vice President of Data and AI, shortly after AWS re:Invent 2024 to hear his impressionsand to get insights on how the latest AWS innovations help meet the real-world needs of customers as they build and scale transformative generative AI applications. Canva uses AWS to power 1.2

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Dataversity

JANUARY 28, 2021

It has been ten years since Pentaho Chief Technology Officer James Dixon coined the term “data lake.” While data warehouse (DWH) systems have had longer existence and recognition, the data industry has embraced the more […]. The post A Bridge Between Data Lakes and Data Warehouses appeared first on DATAVERSITY.

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IBM Journey to AI blog

SEPTEMBER 19, 2023

Though you may encounter the terms “data science” and “data analytics” being used interchangeably in conversations or online, they refer to two distinctly different concepts. Meanwhile, data analytics is the act of examining datasets to extract value and find answers to specific questions.

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Pickl AI

NOVEMBER 15, 2023

Discover the nuanced dissimilarities between Data Lakes and Data Warehouses. Data management in the digital age has become a crucial aspect of businesses, and two prominent concepts in this realm are Data Lakes and Data Warehouses. It acts as a repository for storing all the data.

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AWS Machine Learning Blog

APRIL 3, 2025

At the heart of this transformation is the OMRON Data & Analytics Platform (ODAP), an innovative initiative designed to revolutionize how the company harnesses its data assets. The robust security features provided by Amazon S3, including encryption and durability, were used to provide data protection.

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phData

SEPTEMBER 19, 2023

With the amount of data companies are using growing to unprecedented levels, organizations are grappling with the challenge of efficiently managing and deriving insights from these vast volumes of structured and unstructured data. What is a Data Lake? Consistency of data throughout the data lake.

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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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AWS Machine Learning Blog

NOVEMBER 12, 2024

He is focused on Big Data, Data Lakes, Streaming and batch Analytics services and generative AI technologies. He works with strategic customers who are using AI/ML to solve complex business problems. Varun Mehta is a Sr. Solutions Architect at AWS.

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Alation

FEBRUARY 20, 2020

Architecturally the introduction of Hadoop, a file system designed to store massive amounts of data, radically affected the cost model of data. Organizationally the innovation of self-service analytics, pioneered by Tableau and Qlik, fundamentally transformed the user model for data analysis. The Rise of the Data Catalog.

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AWS Machine Learning Blog

NOVEMBER 15, 2023

Principal is conducting enterprise-scale near-real-time analytics to deliver a seamless and hyper-personalized omnichannel customer experience on their mission to make financial security accessible for all. They are processing data across channels, including recorded contact center interactions, emails, chat and other digital channels.

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Data Science Dojo

SEPTEMBER 10, 2024

These AI models are trained on massive datasets of text and code, enabling them to generate human-quality text, translate languages, write different kinds of creative content, and answer your questions in an informative way. OpenAI’s Contributions to LLM Development Some prominent LLM contributions by Open AI include: GPT-3.5

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ODSC - Open Data Science

JUNE 7, 2023

To make your data management processes easier, here’s a primer on data lakes, and our picks for a few data lake vendors worth considering. What is a data lake? First, a data lake is a centralized repository that allows users or an organization to store and analyze large volumes of data.

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ODSC - Open Data Science

JUNE 1, 2023

Real-Time ML with Spark and SBERT, AI Coding Assistants, Data Lake Vendors, and ODSC East Highlights Getting Up to Speed on Real-Time Machine Learning with Spark and SBERT Learn more about real-time machine learning by using this approach that uses Apache Spark and SBERT. Is an AI Coding Assistant Right For You?

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Precisely

JUNE 24, 2024

The Precisely team recently had the privilege of hosting a luncheon at the Gartner Data & Analytics Summit in London. It was an engaging gathering of industry leaders from various sectors, who exchanged valuable insights into crucial aspects of data governance, strategy, and innovation.

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Flipboard

DECEMBER 18, 2023

Amazon Redshift powers data-driven decisions for tens of thousands of customers every day with a fully managed, AI-powered cloud data warehouse, delivering the best price-performance for your analytics workloads.

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ODSC - Open Data Science

AUGUST 31, 2023

Visualization for Clustering Methods Clustering methods are a big part of data science, and here’s a primer on how you can visualize them. Lemley on Generative AI and the Law Here’s what Mark A. Lemley, law Professor at Stanford, thinks about legal issues that arise from generative AI, the memorization problem, and more.

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Data Science Connect

JULY 28, 2023

As the Internet of Things (IoT) continues to revolutionize industries and shape the future, data scientists play a crucial role in unlocking its full potential. A recent article on Analytics Insight explores the critical aspect of data engineering for IoT applications.

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Dataversity

OCTOBER 14, 2022

The data being talked about is useful for businesses to draw insights, formulate strategies, and understand trends and customer behavior, among others. […]. The post Maximize the ROI of Your Enterprise Data Lake appeared first on DATAVERSITY.

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IBM Journey to AI blog

OCTOBER 4, 2023

Artificial intelligence (AI) is now at the forefront of how enterprises work with data to help reinvent operations, improve customer experiences, and maintain a competitive advantage. It’s no longer a nice-to-have, but an integral part of a successful data strategy. Why does AI need an open data lakehouse architecture?

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ODSC - Open Data Science

SEPTEMBER 29, 2023

Data management problems can also lead to data silos; disparate collections of databases that don’t communicate with each other, leading to flawed analysis based on incomplete or incorrect datasets. One way to address this is to implement a data lake: a large and complex database of diverse datasets all stored in their original format.

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AWS Machine Learning Blog

AUGUST 8, 2024

As one of the largest AWS customers, Twilio engages with data, artificial intelligence (AI), and machine learning (ML) services to run their daily workloads. Data is the foundational layer for all generative AI and ML applications. The following diagram illustrates the solution architecture.

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ODSC - Open Data Science

MARCH 21, 2025

In todays fast-paced data-driven world, open-source solutions are transforming industries by providing flexible, scalable, and community-driven innovations. Whether youre a data scientist, engineer, or AI researcher, tapping into open-source technologies can accelerate your work while fostering collaboration.

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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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Smart Data Collective

DECEMBER 13, 2022

However, computerization in the digital age creates massive volumes of data, which has resulted in the formation of several industries, all of which rely on data and its ever-increasing relevance. Data analytics and visualization help with many such use cases. It is the time of big data. What Is Data Analytics?

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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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AWS Machine Learning Blog

OCTOBER 20, 2023

Recent developments in generative AI models have further sped up the need of ML adoption across industries. However, implementing security, data privacy, and governance controls are still key challenges faced by customers when implementing ML workloads at scale.

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Precisely

OCTOBER 16, 2023

Rapid advancements in digital technologies are transforming cloud-based computing and cloud analytics. Big data analytics, IoT, AI, and machine learning are revolutionizing the way businesses create value and competitive advantage. In a connected mainframe/cloud environment, data is often diverse and fragmented.

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IBM Journey to AI blog

APRIL 24, 2023

By running reports on historical data, a data warehouse can clarify what systems and processes are working and what methods need improvement. Data warehouse is the base architecture for artificial intelligence and machine learning (AI/ML) solutions as well. Modern data warehousing technology can handle all data forms.

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IBM Journey to AI blog

APRIL 15, 2024

An inaccurate AI prediction in a marketing campaign is a minor nuisance, but an inaccurate AI prediction on a manufacturing shopfloor can be fatal. Or we create a data lake, which quickly degenerates to a data swamp. Summarization Summarization remains the top use case for generative AI (gen AI) technology.

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