AWS Big Data

SEPTEMBER 13, 2023

A modern data architecture is an evolutionary architecture pattern designed to integrate a data lake, data warehouse, and purpose-built stores with a unified governance model. The company wanted the ability to continue processing operational data in the secondary Region in the rare event of primary Region failure.

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Data Lake Data Processing Metadata Snapshot 111

AWS Big Data

OCTOBER 30, 2024

Amazon DataZone now launched authentication supports through the Amazon Athena JDBC driver, allowing data users to seamlessly query their subscribed data lake assets via popular business intelligence (BI) and analytics tools like Tableau, Power BI, Excel, SQL Workbench, DBeaver, and more.

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Visualization Data Lake Testing Data Governance 119

AWS Big Data

OCTOBER 14, 2024

Enterprise data is brought into data lakes and data warehouses to carry out analytical, reporting, and data science use cases using AWS analytical services like Amazon Athena , Amazon Redshift , Amazon EMR , and so on. Even for the same prompt definition, the model provided a varying list of attributes.

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Metadata Data Lake Modeling Data Warehouse 105

AWS Big Data

OCTOBER 30, 2024

With this integration, you can now seamlessly query your governed data lake assets in Amazon DataZone using popular business intelligence (BI) and analytics tools, including partner solutions like Tableau. Refer to the detailed blog post on how you can use this to connect through various other tools.

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Analytics Visualization Data Governance Data-driven 119

CIO Business Intelligence

OCTOBER 23, 2024

We pulled these people together, and defined use cases we could all agree were the best to demonstrate our new data capability. Once they were identified, we had to determine we had the right data. Then we migrated the data to our new data lake, and stood up the new platform.

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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. availability. impl":"org.apache.iceberg.aws.s3.S3FileIO", parquet") df.sortWithinPartitions("review_date").writeTo("dev.db.amazon_reviews_iceberg").append()

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Data Lake Snapshot Metadata Optimization 98

CIO Business Intelligence

APRIL 8, 2025

Yet, despite growing investments in advanced analytics and AI, organizations continue to grapple with a persistent and often underestimated challenge: poor data quality. Fragmented systems, inconsistent definitions, legacy infrastructure and manual workarounds introduce critical risks.

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Data Quality Data-driven Key Performance Indicator Metadata 102

Jet Global

JULY 2, 2019

To address the flood of data and the needs of enterprise businesses to store, sort, and analyze that data, a new storage solution has evolved: the data lake. What’s in a Data Lake? Data warehouses do a great job of standardizing data from disparate sources for analysis. Taking a Dip.

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AWS Big Data

NOVEMBER 7, 2024

Generative SQL uses query history for better accuracy, and you can further improve accuracy through custom context, such as table descriptions, column descriptions, foreign key and primary key definitions, and sample queries. Let’s ask Amazon Q to “Show me the unconverted mana cost and name for all the cards created by Rob Alexander.”

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Metadata Sales Data Warehouse Optimization 105

DataKitchen

JANUARY 25, 2022

For example, DataOps can be used to automate data integration. Previously, the consulting team had been using a patchwork of ETL to consolidate data from disparate sources into a data lake. It definitely means redeploying internal and outsourcing budgets to higher value-add activities.

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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 Machine Learning Cost-Benefit 98

AWS Big Data

JUNE 15, 2023

In today’s world, customers manage vast amounts of data in their Amazon Simple Storage Service (Amazon S3) data lakes, which requires convoluted data pipelines to continuously understand the changes in the data layout and make them available to consuming systems.

Data Lake 105

Data Lake Metadata Cost-Benefit Management 105

AWS Big Data

AUGUST 8, 2024

Today’s data lakes are expanding across lines of business operating in diverse landscapes and using various engines to process and analyze data. Traditionally, SQL views have been used to define and share filtered data sets that meet the requirements of these lines of business for easier consumption.

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Data Lake Sales Marketing Big Data 120

AWS Big Data

NOVEMBER 22, 2023

Apache Hudi is an open table format that brings database and data warehouse capabilities to data lakes. Apache Hudi helps data engineers manage complex challenges, such as managing continuously evolving datasets with transactions while maintaining query performance. Under Administration , choose Data catalog settings.

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Data Lake Snapshot Metadata Optimization 116

IBM Big Data Hub

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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Data Lake Metadata Cost-Benefit Data Warehouse 60

O'Reilly on Data

OCTOBER 19, 2021

While there isn’t an authoritative definition for the term, it shares its ethos with its predecessor, the DevOps movement in software engineering: by adopting well-defined processes, modern tooling, and automated workflows, we can streamline the process of moving from development to robust production deployments.

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AWS Big Data

NOVEMBER 29, 2023

It enables data engineers, data scientists, and analytics engineers to define the business logic with SQL select statements and eliminates the need to write boilerplate data manipulation language (DML) and data definition language (DDL) expressions.

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Data Lake Management Metrics Data Warehouse 122

Alation

FEBRUARY 20, 2020

When it was no longer a hard requirement that a physical data model be created upon the ingestion of data, there was a resulting drop in richness of the description and consistency of the data stored in Hadoop. You did not have to understand or prepare the data to get it into Hadoop, so people rarely did.

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Data Lake Metadata Structured Data Big Data 52

CIO Business Intelligence

APRIL 10, 2025

To achieve this, SAP must continuously harmonize its product landscape and consistently implement uniform standards, for example, in data models and identity and security services, said DSAG CTO Sebastian Westphal. After all, many SAP users have already implemented modern data lake and data lakehouse architectures.

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Strategy Cost-Benefit Data Lake Modeling 73

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. Data Modeling.

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Data Lake Modeling Unstructured Data Data Warehouse 52

AWS Big Data

MARCH 1, 2024

One of the bank’s key challenges related to strict cybersecurity requirements is to implement field level encryption for personally identifiable information (PII), Payment Card Industry (PCI), and data that is classified as high privacy risk (HPR). Only users with required permissions are allowed to access data in clear text.

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Data Lake Data Warehouse Management Risk 119

CIO Business Intelligence

OCTOBER 25, 2022

The variables seem endless: data— security , science , storage , mining , management , definition , deletion , integration , accessibility , architecture , collection , governance , and the ever-elusive, data culture. So, they built a data-lake. The data lake, too, took on new purpose.

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CIO Business Intelligence

APRIL 25, 2024

“The challenge that a lot of our customers have is that requires you to copy that data, store it in Salesforce; you have to create a place to store it; you have to create an object or field in which to store it; and then you have to maintain that pipeline of data synchronization and make sure that data is updated,” Carlson said.

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Data Integration Data Lake Data Warehouse Metadata 119

AWS Big Data

NOVEMBER 7, 2024

Tens of thousands of customers use Amazon Redshift every day to run analytics, processing exabytes of data for business insights. times better price performance than other cloud data warehouses. Amazon Redshift is built for scale and delivers up to 7.9

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Data Warehouse Reporting Big Data Data Lake 105

AWS Big Data

OCTOBER 10, 2023

Data governance is the process of ensuring the integrity, availability, usability, and security of an organization’s data. Due to the volume, velocity, and variety of data being ingested in data lakes, it can get challenging to develop and maintain policies and procedures to ensure data governance at scale for your data lake.

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Data Quality Data Governance Data Lake Testing 111

DataKitchen

OCTOBER 11, 2021

First, you must understand the existing challenges of the data team, including the data architecture and end-to-end toolchain. Second, you must establish a definition of “done.” In DataOps, the definition of done includes more than just some working code. Definition of Done. When can you declare it done?

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Testing Metadata Dashboards Statistics 152

Cloudera

MARCH 31, 2021

Customers who have chosen Google Cloud as their cloud platform can now use CDP Public Cloud to create secure governed data lakes in their own cloud accounts and deliver security, compliance and metadata management across multiple compute clusters. Data Preparation (Apache Spark and Apache Hive) .

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Data Lake Metadata Enterprise Analytics 94

AWS Big Data

MARCH 20, 2023

In the first post of this series , we described how AWS Glue for Apache Spark works with Apache Hudi, Linux Foundation Delta Lake, and Apache Iceberg datasets tables using the native support of those data lake formats. Even without prior experience using Hudi, Delta Lake or Iceberg, you can easily achieve typical use cases.

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Visualization Data Lake Snapshot Big Data 98

AWS Big Data

AUGUST 16, 2023

Iceberg has become very popular for its support for ACID transactions in data lakes and features like schema and partition evolution, time travel, and rollback. If this is the first time accessing the Lake Formation console, add yourself as the data lake administrator. Now you can set up Lake Formation permissions.

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Data Lake Metadata Snapshot Management 98

Timo Elliott

MAY 27, 2022

I was at the Gartner Data & Analytics conference in London a couple of weeks ago and I’d like to share some thoughts on what I think was interesting, and what I think I learned…. First, data is by default, and by definition, a liability , because it costs money and has risks associated with it.

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Data Analytics Analytics Recreation/Entertainment Data Lake 124

AWS Big Data

NOVEMBER 20, 2023

Use case A typical workload for AWS Glue for Apache Spark jobs is to load data from a relational database to a data lake with SQL-based transformations. The following is a visual representation of an example job where the number of workers is 10. On the Graphed metrics tab, configure your preferred statistic, period, and so on.

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Metrics Data Lake Cost-Benefit Dashboards 127

AWS Big Data

DECEMBER 13, 2023

For the past 5 years, BMS has used a custom framework called Enterprise Data Lake Services (EDLS) to create ETL jobs for business users. About the authors Sivaprasad Mahamkali is a Senior Streaming Data Engineer at AWS Professional Services. Shovan works with customers to design data and machine learning solutions on AWS.

Metadata 111

Metadata Data Lake Visualization Data Quality 111

Cloudera

NOVEMBER 5, 2020

When you register an Environment in CDP, a Data Lake is automatically deployed for that environment. Data Lake security and governance is managed by a shared set of services running within a Data Lake cluster. These are the shared security services encompassed within SDX. .

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Data Lake Data Warehouse Metadata Optimization 74

AWS Big Data

JUNE 21, 2023

When setting out to build a data warehouse, it’s a common pattern to have a data lake as the source of the data warehouse. The data lake in this context serves a number of important functions: It acts as a central source for multiple applications, not just exclusively for data warehousing purposes.

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Data Warehouse Data Lake OLAP Cost-Benefit 105

AWS Big Data

DECEMBER 21, 2023

To bring their customers the best deals and user experience, smava follows the modern data architecture principles with a data lake as a scalable, durable data store and purpose-built data stores for analytical processing and data consumption.

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erwin

DECEMBER 17, 2020

By having a single definition of something, complex ETL doesn’t have to be performed repeatedly. Once something is defined, then then everyone can map to the standard definition of what the data means. Compliance: It improves data governance to comply with such regulations as the General Data Protection Regulation (GDPR).

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Modeling Metadata Data-driven Data Lake 90

AWS Big Data

JANUARY 24, 2023

This solution only replicates metadata in the Data Catalog, not the actual underlying data. To have a redundant data lake using Lake Formation and AWS Glue in an additional Region, we recommend replicating the Amazon S3-based storage using S3 replication , S3 sync, aws-s3-copy-sync-using-batch or S3 Batch replication process.

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