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 106

Data Lake Big Data OLAP Testing 106

DataKitchen

NOVEMBER 4, 2021

Cloud computing has made it much easier to integrate data sets, but that’s only the beginning. Creating a data lake has become much easier, but that’s only ten percent of the job of delivering analytics to users. It often takes months to progress from a data lake to the final delivery of insights.

Data Processing 246

Data Processing Data Lake Cost-Benefit Testing 246

AWS Big Data

SEPTEMBER 26, 2024

For many organizations, this centralized data store follows a data lake architecture. Although data lakes provide a centralized repository, making sense of this data and extracting valuable insights can be challenging. We recommend testing your use case and data with different models.

Data Lake 115

Data Lake Cost-Benefit Unstructured Data Modeling 115

AWS Big Data

JUNE 10, 2024

Enterprises and organizations across the globe want to harness the power of data to make better decisions by putting data at the center of every decision-making process. The open table format accelerates companies’ adoption of a modern data strategy because it allows them to use various tools on top of a single copy of the data.

Data Lake 126

Data Lake Metadata Snapshot Analytics 126

AWS Big Data

AUGUST 9, 2023

The combination of a data lake in a serverless paradigm brings significant cost and performance benefits. By monitoring application logs, you can gain insights into job execution, troubleshoot issues promptly to ensure the overall health and reliability of data pipelines.

Data Lake 98

Data Lake Metrics Testing Cost-Benefit 98

DataKitchen

AUGUST 19, 2021

Data mesh and DataOps provide the organization, enterprise architecture, and workflow automation that together enable a relatively small data team to address the analytics needs of hundreds of active business users. Figure 1: Data requirements for phases of the drug product lifecycle. The new Recipes run, and BOOM!

Data Warehouse 246

Data Warehouse Data Lake Manufacturing Testing 246

AWS Big Data

JUNE 10, 2024

Use cases for Hive metastore federation for Amazon EMR Hive metastore federation for Amazon EMR is applicable to the following use cases: Governance of Amazon EMR-based data lakes – Producers generate data within their AWS accounts using an Amazon EMR-based data lake supported by EMRFS on Amazon Simple Storage Service (Amazon S3)and HBase.

Data Lake 117

Data Lake Metadata Data Warehouse Data Processing 117

DataKitchen

JANUARY 25, 2022

There’s no shortage of consultants who will promise to manage the end-to-end lifecycle of data from integration to transformation to visualization. . The challenge is that data engineering and analytics are incredibly complex. The data requirements of a thriving business are never complete.

Consulting 244

Consulting Testing Data Lake Data Quality 244

DataKitchen

AUGUST 3, 2021

The data mesh design pattern breaks giant, monolithic enterprise data architectures into subsystems or domains, each managed by a dedicated team. But first, let’s define the data mesh design pattern. The past decades of enterprise data platform architectures can be summarized in 69 words.

Data Architecture 246

Data Architecture Data Lake Cost-Benefit Data Warehouse 246

O'Reilly on Data

OCTOBER 19, 2021

This is both frustrating for companies that would prefer making ML an ordinary, fuss-free value-generating function like software engineering, as well as exciting for vendors who see the opportunity to create buzz around a new category of enterprise software. An Overarching Concern: Correctness and Testing. Why did something break?

IT 364

IT Testing Experimentation Software 364

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.

Data Lake 111

Data Lake Data Processing Metadata Snapshot 111

AWS Big Data

OCTOBER 30, 2024

Amazon DataZone recently announced the expansion of data analysis and visualization options for your project-subscribed data within Amazon DataZone using the Amazon Athena JDBC driver. Joel has led data transformation projects on fraud analytics, claims automation, and Master Data Management. Follow him on LinkedIn.

Analytics 119

Analytics Visualization Data Governance Data-driven 119

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.

Data Lake 98

Data Lake Metadata Testing Data Warehouse 98

Corinium

JUNE 6, 2019

Lack of clear, unified, and scaled data engineering expertise to enable the power of AI at enterprise scale. Some of the work is very foundational, such as building an enterprise data lake and migrating it to the cloud, which enables other more direct value-added activities such as self-service.

Insurance 250

Insurance Analytics Forecasting Deep Learning 250

Jet Global

SEPTEMBER 4, 2020

There is an established body of practice around creating, managing, and accessing OLAP data (known as “cubes”). Data Lakes. There has been a lot of talk over the past year or two in the D365F&SCM world about “data lakes.” Traditional databases and data warehouses do not lend themselves to that task.

Data Lake 88

Data Lake OLAP Data Warehouse Unstructured Data 88

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 98

Data Lake Snapshot Metadata Optimization 98

DataKitchen

JANUARY 3, 2022

The data analytics function in large enterprises is generally distributed across departments and roles. For example, teams working under the VP/Directors of Data Analytics may be tasked with accessing data, building databases, integrating data, and producing reports. Analytics Hub and Spoke. DataOps Process Hub.

Business Analytics 245

Business Analytics Analytics Testing Dashboards 245

AWS Big Data

JANUARY 9, 2025

These features allow efficient data corrections, gap-filling in time series, and historical data updates without disrupting ongoing analyses or compromising data integrity. Unlike direct Amazon S3 access, Iceberg supports these operations on petabyte-scale data lakes without requiring complex custom code.

Metadata 111

Metadata Snapshot Cost-Benefit Optimization 111

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.

Enterprise 104

Enterprise Data Lake Data Collection Data-driven 104

datapine

APRIL 15, 2020

Your Chance: Want to test an agile business intelligence solution? It’s necessary to say that these processes are recurrent and require continuous evolution of reports, online data visualization , dashboards, and new functionalities to adapt current processes and develop new ones. Finalize testing. Train end-users.

Business Intelligence 276

Business Intelligence Analytics Testing Dashboards 276

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. Has the data arrived on time?

Analytics 246

Analytics Sales Testing Cost-Benefit 246

AWS Big Data

MAY 29, 2024

Many organizations use external identity providers (IdPs) such as Okta or Microsoft Azure Active Directory to manage their enterprise user identities. Provide a database name ( tip-blog-redshift-ds-db ), which will be created in the Data Catalog by Lake Formation. In this post, we grant access to Group1.

Data Lake 116

Data Lake Enterprise Management Business Intelligence 116

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.

Data Lake 98

Data Lake Data Warehouse Marketing Management 98

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 111

Enterprise Data Warehouse Data Lake Optimization 111

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. A question arises on what level of details we need to include in the table metadata.

Metadata 105

Metadata Data Lake Modeling Data Warehouse 105

CIO Business Intelligence

APRIL 8, 2025

I aim to outline pragmatic strategies to elevate data quality into an enterprise-wide capability. Key recommendations include investing in AI-powered cleansing tools and adopting federated governance models that empower domains while ensuring enterprise alignment. Inflexible schema, poor for unstructured or real-time data.

Data Quality 102

Data Quality Data-driven Key Performance Indicator Metadata 102

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 130

Enterprise Consulting Modeling Cost-Benefit 130

CIO Business Intelligence

JULY 13, 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.

Enterprise 88

Enterprise Data Lake Data Collection Data-driven 88

AWS Big Data

NOVEMBER 22, 2024

Testing these upgrades involves running the application and addressing issues as they arise. Each test run may reveal new problems, resulting in multiple iterations of changes. They then need to modify their Spark scripts and configurations, updating features, connectors, and library dependencies as needed. Python 3.7) to Spark 3.3.0

Cost-Benefit 105

Cost-Benefit Data-driven Software Testing 105

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 111

Enterprise Data Warehouse Snapshot Cost-Benefit 111

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.

Snapshot 132

Snapshot Data Lake Metadata Recreation/Entertainment 132

CIO Business Intelligence

NOVEMBER 25, 2022

Today, more than 90% of its applications run in the cloud, with most of its data is housed and analyzed in a homegrown enterprise data warehouse. Like many CIOs, Carhartt’s top digital leader is aware that data is the key to making advanced technologies work. Today, we backflush our data lake through our data warehouse.

Data Lake 128

Data Lake Data Warehouse Unstructured Data Data Architecture 128

erwin

OCTOBER 8, 2020

By using automated and repeatable capabilities, you can quickly and safely migrate data to the cloud and govern it along the way. But transforming and migrating enterprise data to the cloud is only half the story – once there, it needs to be governed for completeness and compliance. GDPR, CCPA, HIPAA, SOX, PIC DSS).

Data Governance 145

Data Governance Metadata Testing Data Lake 145

AWS Big Data

JULY 3, 2023

Terminology Let’s first discuss some of the terminology used in this post: Research data lake on Amazon S3 – A data lake is a large, centralized repository that allows you to manage all your structured and unstructured data at any scale.

Snapshot 105

Snapshot Data Lake Testing Strategy 105

Smart Data Collective

OCTOBER 17, 2022

A point of data entry in a given pipeline. Examples of an origin include storage systems like data lakes, data warehouses and data sources that include IoT devices, transaction processing applications, APIs or social media. The final point to which the data has to be eventually transferred is a destination.

Data Warehouse 145

Data Warehouse Data Lake Visualization Big Data 145

AWS Big Data

OCTOBER 9, 2024

Today, customers are embarking on data modernization programs by migrating on-premises data warehouses and data lakes to the AWS Cloud to take advantage of the scale and advanced analytical capabilities of the cloud. Compare ongoing data that is replicated from the source on-premises database to the target S3 data lake.

Data Quality 115

Data Quality Data Lake Data Warehouse Metrics 115

AWS Big Data

FEBRUARY 16, 2024

Many customers are extending their data warehouse capabilities to their data lake with Amazon Redshift. They are looking to further enhance their security posture where they can enforce access policies on their data lakes based on Amazon Simple Storage Service (Amazon S3). Choose Create endpoint.

Data Lake 119

Data Lake Data Warehouse Testing Business Objectives 119