Pickl AI

SEPTEMBER 17, 2024

Summary: This blog delves into the multifaceted world of Big Data, covering its defining characteristics beyond the 5 V’s, essential technologies and tools for management, real-world applications across industries, challenges organisations face, and future trends shaping the landscape.

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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. Subscribe to Alation's Blog.

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Data Lakes Hadoop Tableau Big Data 52

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. Big Data Architect.

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Pickl AI

AUGUST 9, 2024

Summary: A comprehensive Big Data syllabus encompasses foundational concepts, essential technologies, data collection and storage methods, processing and analysis techniques, and visualisation strategies. Fundamentals of Big Data Understanding the fundamentals of Big Data is crucial for anyone entering this field.

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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

NOVEMBER 12, 2024

In this blog post, we demonstrate prompt engineering techniques to generate accurate and relevant analysis of tabular data using industry-specific language. This is done by providing large language models (LLMs) in-context sample data with features and labels in the prompt. Arghya Banerjee is a Sr.

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The Data Administration Newsletter

JUNE 5, 2024

In the ever-evolving landscape of data management, two key concepts have emerged as essential components for organizations seeking to harness the power of their data: data marts and data lakes. Understanding the distinctions […]

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phData

NOVEMBER 8, 2024

Open Table Format (OTF) architecture now provides a solution for efficient data storage, management, and processing while ensuring compatibility across different platforms. In this blog, we will discuss: What is the Open Table format (OTF)? It can also be integrated into major data platforms like Snowflake.

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Pickl AI

SEPTEMBER 18, 2024

Summary: Netflix’s sophisticated Big Data infrastructure powers its content recommendation engine, personalization, and data-driven decision-making. As a pioneer in the streaming industry, Netflix utilises advanced data analytics to enhance user experience, optimise operations, and drive strategic decisions.

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AWS Machine Learning Blog

AUGUST 8, 2024

Managing and retrieving the right information can be complex, especially for data analysts working with large data lakes and complex SQL queries. This post highlights how Twilio enabled natural language-driven data exploration of business intelligence (BI) data with RAG and Amazon Bedrock.

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SQL Data Lakes Data Analyst AWS 133

IBM Journey to AI blog

APRIL 24, 2023

Managing, storing, and processing data is critical to business efficiency and success. Modern data warehousing technology can handle all data forms. Significant developments in big data, cloud computing, and advanced analytics created the demand for the modern data warehouse.

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DagsHub

DECEMBER 11, 2023

Best 8 data version control tools for 2023 (Source: DagsHub ) Introduction With business needs changing constantly and the growing size and structure of datasets, it becomes challenging to efficiently keep track of the changes made to the data, which leads to unfortunate scenarios such as inconsistencies and errors in data.

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AWS Machine Learning Blog

OCTOBER 20, 2023

Data and governance foundations – This function uses a data mesh architecture for setting up and operating the data lake, central feature store, and data governance foundations to enable fine-grained data access. This framework considers multiple personas and services to govern the ML lifecycle at scale.

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IBM Journey to AI blog

OCTOBER 4, 2023

A data lakehouse architecture combines the performance of data warehouses with the flexibility of data lakes, to address the challenges of today’s complex data landscape and scale AI. How does an open data lakehouse architecture support AI? All of this supports the use of AI.

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Smart Data Collective

FEBRUARY 20, 2022

Data storage databases. Your SaaS company can store and protect any amount of data using Amazon Simple Storage Service (S3), which is ideal for data lakes, cloud-native applications, and mobile apps. This blog post has demonstrated how AWS can greatly benefit your SaaS company, on multiple levels. Conclusions.

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IBM Journey to AI blog

JUNE 15, 2023

It is comprised of commodity cloud object storage, open data and open table formats, and high-performance open-source query engines. To help organizations scale AI workloads, we recently announced IBM watsonx.data , a data store built on an open data lakehouse architecture and part of the watsonx AI and data platform.

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ODSC - Open Data Science

MAY 7, 2024

Known for his thought leadership in the realm of Big Data and advanced analytics, James specializes in contemporary data architectures including the modern data warehouse, data lakehouse, data fabric, and data mesh. James Serra discusses data lakehouses, which merge data lakes and data warehouses.

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Data Warehouse Data Lakes Data Science Big Data 52

AWS Machine Learning Blog

AUGUST 21, 2023

You can streamline the process of feature engineering and data preparation with SageMaker Data Wrangler and finish each stage of the data preparation workflow (including data selection, purification, exploration, visualization, and processing at scale) within a single visual interface.

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AWS Machine Learning Blog

FEBRUARY 21, 2025

He specializes in large language models, cloud infrastructure, and scalable data systems, focusing on building intelligent solutions that enhance automation and data accessibility across Amazons operations. Chaithanya Maisagoni is a Senior Software Development Engineer (AI/ML) in Amazons Worldwide Returns and ReCommerce organization.

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AWS Machine Learning Blog

AUGUST 21, 2024

Amazon DataZone is a data management service that makes it quick and convenient to catalog, discover, share, and govern data stored in AWS, on-premises, and third-party sources. The data lake environment is required to configure an AWS Glue database table, which is used to publish an asset in the Amazon DataZone catalog.

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Machine Learning Machine Learning Data Governance ML 128

Alation

FEBRUARY 13, 2020

A lot of people in our audience are looking at implementing data lakes or are in the middle of big data lake initiatives. I know in February of 2017 Munich Re launched their own innovative platform as a cornerstone for analytics that involved a big data lake and a data catalog.

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Alation

FEBRUARY 13, 2020

This brief definition makes several points about data catalogs—data management, searching, data inventory, and data evaluation—but all depend on the central capability to provide a collection of metadata. Data catalogs have become the standard for metadata management in the age of big data and self-service analytics.

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phData

SEPTEMBER 20, 2023

This blog was originally written by Keith Smith and updated for 2023 by Nick Goble & Dominick Rocco. You’ve probably heard of the Snowflake Data Cloud , but did you know that Snowflake also offers a revolutionary set of libraries and runtimes called Snowpark? What is Snowflake’s Snowpark? This can be a major optimization.

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SQL Python Data Lakes Machine Learning 98

IBM Journey to AI blog

MAY 19, 2023

With high-speed file transfer, integrated services and cross-region offerings, IBM Cloud Object Storage allows you to leverage your data securely. In addition, it helps to reduce backup costs, provide permanent access to archived data, store data for cloud-native applications and create data lakes for big data analytics and AI.

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AWS Machine Learning Blog

AUGUST 15, 2024

You can use the advanced search and filter option in SageMaker Canvas to select columns that are of String data type to simplify the process. Refer to the SageMaker Canvas blog for other examples using SageMaker Data Wrangler. He has a background in AI/ML & big data.

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Dataversity

JANUARY 6, 2021

We live in an era of big data. Amazingly, statistics show that around 90 percent of this data is only two years old. However, Data Management and structuring are notoriously complex. […]. The post The Need for Flexible Data Management: Why Is Data Flexibility So Important?

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AWS Machine Learning Blog

DECEMBER 4, 2023

Esra Kayabalı is a Senior Solutions Architect at AWS, specialized in the analytics domain, including data warehousing, data lakes, big data analytics, batch and real-time data streaming, and data integration. She has worked on commercial, supply chain, and discovery-related projects.

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Dataversity

FEBRUARY 24, 2021

The amount of data generated in the digital world is increasing by the minute! This massive amount of data is termed “big data.” We may classify the data as structured, unstructured, or semi-structured. Data that is structured or semi-structured is relatively easy to store, process, and analyze. […].

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IBM Journey to AI blog

SEPTEMBER 19, 2023

To pursue a data science career, you need a deep understanding and expansive knowledge of machine learning and AI. And you should have experience working with big data platforms such as Hadoop or Apache Spark. Your skill set should include the ability to write in the programming languages Python, SAS, R and Scala.

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Flipboard

JUNE 26, 2023

Companies are faced with the daunting task of ingesting all this data, cleansing it, and using it to provide outstanding customer experience. Typically, companies ingest data from multiple sources into their data lake to derive valuable insights from the data.

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AWS Machine Learning Blog

JANUARY 4, 2024

In entered the Big Data space in 2013 and continues to explore that area. Arghya is focused on Big Data, Data Lakes, Streaming, Batch Analytics and AI/ML services and technologies. He also holds an MBA from Colorado State University. Arghya Banerjee is a Sr.

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Pickl AI

JULY 30, 2024

Its architecture includes FlowFiles, repositories, and processors, enabling efficient data processing and transformation. With a user-friendly interface and robust features, NiFi simplifies complex data workflows and enhances real-time data integration. What is Apache NiFi?

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IBM Journey to AI blog

JANUARY 5, 2023

The first generation of data architectures represented by enterprise data warehouse and business intelligence platforms were characterized by thousands of ETL jobs, tables, and reports that only a small group of specialized data engineers understood, resulting in an under-realized positive impact on the business.

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Data Quality Data Lakes Data Warehouse Big Data 52

AWS Machine Learning Blog

DECEMBER 18, 2023

Prior joining AWS, as a Data/Solution Architect he implemented many projects in Big Data domain, including several data lakes in Hadoop ecosystem. As a Data Engineer he was involved in applying AI/ML to fraud detection and office automation.

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AWS Machine Learning Blog

DECEMBER 7, 2023

Esra Kayabalı is a Senior Solutions Architect at AWS, specializing in the analytics domain including data warehousing, data lakes, big data analytics, batch and real-time data streaming and data integration. He loves combining open-source projects with cloud services.

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DataRobot Blog

OCTOBER 3, 2017

With this integration, customers can now harness the full power of Azure’s Big Data offerings in a self-service manner to gain immediate value.”. This highlights the two companies’ shared vision on self-service data discovery with an emphasis on collaboration and data governance.

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Alation

FEBRUARY 13, 2020

In an earlier blog, I defined a data catalog as “a collection of metadata, combined with data management and search tools, that helps analysts and other data users to find the data that they need, serves as an inventory of available data, and provides information to evaluate fitness data for intended uses.”.

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