AWS Big Data

SEPTEMBER 13, 2023

The Analytics specialty practice of AWS Professional Services (AWS ProServe) helps customers across the globe with modern data architecture implementations on the AWS Cloud. Of those tables, some are larger (such as in terms of record volume) than others, and some are updated more frequently than others.

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Data Lake Data Processing Metadata Snapshot 89

Analytics Vidhya

OCTOBER 10, 2022

Introduction In the modern data world, Lakehouse has become one of the most discussed topics for building a data platform. Enterprises have slowly started adopting Lakehouses for their data ecosystems as they offer cost efficiencies of data lakes and the performance of warehouses. […].

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Data Lake Data Science Publishing Enterprise 341

AWS Big Data

MARCH 10, 2023

Since the deluge of big data over a decade ago, many organizations have learned to build applications to process and analyze petabytes of data. Data lakes have served as a central repository to store structured and unstructured data at any scale and in various formats.

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Data Lake Sales Data Warehouse Snapshot 100

David Menninger's Analyst Perspectives

FEBRUARY 21, 2024

Unstructured data has been a significant factor in data lakes and analytics for some time. Twelve years ago, nearly a third of enterprises were working with large amounts of unstructured data. As I’ve pointed out previously , unstructured data is really a misnomer.

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Unstructured Data Data Lake Enterprise Technology 144

Data Virtualization

MARCH 16, 2023

Reading Time: 6 minutes Data lake, by combining the flexibility of object storage with the scalability and agility of cloud platforms, are becoming an increasingly popular choice as an enterprise data repository. Whether you are on Amazon Web Services (AWS) and leverage AWS S3.

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Data Lake Strategy Data Integration Enterprise 52

Data Virtualization

MARCH 16, 2023

Reading Time: 6 minutes Data lake, by combining the flexibility of object storage with the scalability and agility of cloud platforms, are becoming an increasingly popular choice as an enterprise data repository. Whether you are on Amazon Web Services (AWS) and leverage AWS S3.

Data Lake 52

Data Lake Strategy Data Integration Enterprise 52

David Menninger's Analyst Perspectives

SEPTEMBER 16, 2021

Rapidminer is a visual enterprise data science platform that includes data extraction, data mining, deep learning, artificial intelligence and machine learning (AI/ML) and predictive analytics. It can support AI/ML processes with data preparation, model validation, results visualization and model optimization.

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AWS Big Data

MARCH 7, 2024

At the same time, they need to optimize operational costs to unlock the value of this data for timely insights and do so with a consistent performance. With this massive data growth, data proliferation across your data stores, data warehouse, and data lakes can become equally challenging.

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Analytics Vidhya

FEBRUARY 27, 2023

Introduction Enterprises here and now catalyze vast quantities of data, which can be a high-end source of business intelligence and insight when used appropriately. Delta Lake allows businesses to access and break new data down in real time.

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AWS Big Data

FEBRUARY 24, 2023

Data lakes are a popular choice for today’s organizations to store their data around their business activities. As a best practice of a data lake design, data should be immutable once stored. A data lake built on AWS uses Amazon Simple Storage Service (Amazon S3) as its primary storage environment.

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Data Lake Metadata Testing Data Warehouse 82

AWS Big Data

MAY 24, 2023

When you build your transactional data lake using Apache Iceberg to solve your functional use cases, you need to focus on operational use cases for your S3 data lake to optimize the production environment. Jupyter Enterprise Gateway 2.6.0, availability. This example is demonstrated on an EMR version emr-6.10.0

Data Lake 83

Data Lake Snapshot Metadata Optimization 83

Jet Global

NOVEMBER 5, 2020

Ostensibly, the new product represents Microsoft’s transition to a newer, more cloud-friendly ERP for midsized enterprises. Option 3: Azure Data Lakes. This leads us to Microsoft’s apparent long-term strategy for D365 F&SCM reporting: Azure Data Lakes. Data lakes are not a mature technology.

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Data Lake OLAP Data Warehouse Unstructured Data 98

AWS Big Data

FEBRUARY 14, 2023

Organizations have chosen to build data lakes on top of Amazon Simple Storage Service (Amazon S3) for many years. A data lake is the most popular choice for organizations to store all their organizational data generated by different teams, across business domains, from all different formats, and even over history.

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Data Lake Statistics Data Architecture Finance 80

BizAcuity

MARCH 29, 2019

Data lakes are centralized repositories that can store all structured and unstructured data at any desired scale. The power of the data lake lies in the fact that it often is a cost-effective way to store data. The power of the data lake lies in the fact that it often is a cost-effective way to store data.

Data Lake 102

Data Lake Unstructured Data Cost-Benefit Data Quality 102

AWS Big Data

JULY 21, 2023

Data-driven organizations treat data as an asset and use it across different lines of business (LOBs) to drive timely insights and better business decisions. This leads to having data across many instances of data warehouses and data lakes using a modern data architecture in separate AWS accounts.

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Data Lake Data Warehouse Marketing Management 85

Jet Global

SEPTEMBER 4, 2020

The Data Warehouse Approach. Data warehouses gained momentum back in the early 1990s as companies dealing with growing volumes of data were seeking ways to make analytics faster and more accessible. There is an established body of practice around creating, managing, and accessing OLAP data (known as “cubes”).

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Data Lake OLAP Data Warehouse Unstructured Data 88

DataKitchen

JANUARY 3, 2022

Their business unit colleagues ask an endless stream of urgent questions that require analytic insights. Business analysts must rapidly deliver value and simultaneously manage fragile and error-prone analytics production pipelines. In business analytics, fire-fighting and stress are common. Analytics Hub and Spoke.

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AWS Big Data

NOVEMBER 13, 2023

Join the AWS Analytics team at AWS re:Invent this year, where new ideas and exciting innovations come together. For those in the data world, this post provides a curated guide for all analytics sessions that you can use to quickly schedule and build your itinerary. A shapeshifting guardian and protector of data like Data Lynx?

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Analytics Data Lake Data Warehouse Data-driven 110

Jet Global

JULY 2, 2019

The sheer scale of data being captured by the modern enterprise has necessitated a monumental shift in how that data is stored. What was at first a data stream has morphed into a data river as enterprise businesses are harvesting reams of data from every conceivable input across every conceivable business function.

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Data Lake Data Warehouse Big Data Machine Learning 73

Smart Data Collective

APRIL 2, 2019

Data Lakes are among the most complex and sophisticated data storage and processing facilities we have available to us today as human beings. Analytics Magazine notes that data lakes are among the most useful tools that an enterprise may have at its disposal when aiming to compete with competitors via innovation.

Data Lake 83

Data Lake Big Data OLAP Testing 83

CIO Business Intelligence

JUNE 29, 2022

Insights hidden in your data are essential for optimizing business operations, finetuning your customer experience, and developing new products — or new lines of business, like predictive maintenance. And as businesses contend with increasingly large amounts of data, the cloud is fast becoming the logical place where analytics work gets done.

Data Lake 110

Data Lake Analytics Data Warehouse Machine Learning 110

AWS Big Data

NOVEMBER 29, 2023

In 2013, Amazon Web Services revolutionized the data warehousing industry by launching Amazon Redshift , the first fully-managed, petabyte-scale, enterprise-grade cloud data warehouse. Amazon Redshift made it simple and cost-effective to efficiently analyze large volumes of data using existing business intelligence tools.

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Data Warehouse Data Lake Analytics Machine Learning 99

Cloudera

JUNE 2, 2022

Since 2015, the Cloudera DataFlow team has been helping the largest enterprise organizations in the world adopt Apache NiFi as their enterprise standard data movement tool. What is the modern data stack? In the modern data stack, there is a diverse set of destinations where data needs to be delivered.

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Enterprise Data Lake Data Collection Data-driven 99

AWS Big Data

NOVEMBER 16, 2023

Amazon Redshift is a popular cloud data warehouse, offering a fully managed cloud-based service that seamlessly integrates with an organization’s Amazon Simple Storage Service (Amazon S3) data lake, real-time streams, machine learning (ML) workflows, transactional workflows, and much more—all while providing up to 7.9x

Enterprise 83

Enterprise Data Warehouse Data Lake Optimization 83

AWS Big Data

APRIL 24, 2023

Building a data lake on Amazon Simple Storage Service (Amazon S3) provides numerous benefits for an organization. However, many use cases, like performing change data capture (CDC) from an upstream relational database to an Amazon S3-based data lake, require handling data at a record level.

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Data Lake Data Governance Cost-Benefit Machine Learning 79

AWS Big Data

APRIL 26, 2024

To enable your workforce users for analytics with fine-grained data access controls and audit data access, you might have to create multiple AWS Identity and Access Management (IAM) roles with different data permissions and map the workforce users to one of those roles. You will not see any applications on this page yet.

Analytics 62

Analytics Data Lake Management Enterprise 62

DataKitchen

AUGUST 27, 2021

DataOps has become an essential methodology in pharmaceutical enterprise data organizations, especially for commercial operations. Companies that implement it well derive significant competitive advantage from their superior ability to manage and create value from data. DataOps Success Story.

Analytics 246

Analytics Sales Testing Cost-Benefit 246

Dataiku

SEPTEMBER 1, 2023

Lately, the concept of data experience has been gaining attention in discussions around the enterprise data stack. As the name suggests, it refers to how people interact with data in enterprise settings. Due to fragmented data setups in these companies, their data lakes have the following characteristics:

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Data Lake Data Analytics Analytics Interactive 69

AWS Big Data

JANUARY 27, 2023

To build a data-driven business, it is important to democratize enterprise data assets in a data catalog. With a unified data catalog, you can quickly search datasets and figure out data schema, data format, and location. Verify all table metadata is stored in the AWS Glue Data Catalog.

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Data Lake Metadata Business Analysis Data-driven 61

AWS Big Data

JUNE 20, 2023

Apache Iceberg is an open table format for very large analytic datasets. It manages large collections of files as tables, and it supports modern analytical data lake operations such as record-level insert, update, delete, and time travel queries. Mikhail specializes in data analytics services.

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Data Lake Data Science Recreation/Entertainment Experimentation 71

erwin

AUGUST 15, 2022

For NoSQL, data lakes, and data lake houses—data modeling of both structured and unstructured data is somewhat novel and thorny. This blog is an introduction to some advanced NoSQL and data lake database design techniques (while avoiding common pitfalls) is noteworthy. Analytical.

Data Lake 52

Data Lake Modeling Unstructured Data Data Warehouse 52

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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Data-driven Data Lake Enterprise Analytics 52

AWS Big Data

MARCH 4, 2024

As enterprises collect increasing amounts of data from various sources, the structure and organization of that data often need to change over time to meet evolving analytical needs. Schema evolution enables adding, deleting, renaming, or modifying columns without needing to rewrite existing data.

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Snapshot Data Lake Metadata Recreation/Entertainment 110

CIO Business Intelligence

SEPTEMBER 21, 2023

Generative AI touches every aspect of the enterprise, and every aspect of society,” says Bret Greenstein, partner and leader of the gen AI go-to-market strategy at PricewaterhouseCoopers. Gen AI is that amplification and the world’s reaction to it is like enterprises and society reacting to the introduction of a foreign body. “We

Enterprise 126

Enterprise Consulting Modeling Cost-Benefit 126

DataKitchen

NOVEMBER 29, 2021

DataOps adoption continues to expand as a perfect storm of social, economic, and technological factors drive enterprises to invest in process-driven innovation. As a result, enterprises will examine their end-to-end data operations and analytics creation workflows. Data Gets Meshier. Rise of the DataOps Engineer.

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