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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AWS Machine Learning Blog

APRIL 3, 2025

Data is one of the most critical assets of many organizations. Theyre constantly seeking ways to use their vast amounts of information to gain competitive advantages. Data governance challenges Maintaining consistent data governance across different systems is crucial but complex.

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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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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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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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Alation

JANUARY 27, 2022

As an organization embraces digital transformation , more data is available to inform decisions. To use that data, decision-makers across the company will need to have access. However, opening the floodgates of information comes with challenges. It can also help prevent data misuse. What is Data Analytics?

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Alation

FEBRUARY 20, 2020

For many enterprises, a hybrid cloud data lake is no longer a trend, but becoming reality. With an on-premise deployment, enterprises have full control over data security, data access, and data governance. Data that needs to be tightly controlled (e.g. The Problem with Hybrid Cloud Environments.

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Alation

FEBRUARY 20, 2020

“The key point is that no organization governs information simply because it can. there has to be a business context, and the increasing realization of this context explains the rise of information stewardship applications.” – May 2018 Gartner Market Guide for Information Stewardship Applications.

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Dataversity

MAY 26, 2022

A data lake becomes a data swamp in the absence of comprehensive data quality validation and does not offer a clear link to value creation. Organizations are rapidly adopting the cloud data lake as the data lake of choice, and the need for validating data in real time has become critical.

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Dataversity

APRIL 23, 2021

Within the Data Management industry, it’s becoming clear that the old model of rounding up massive amounts of data, dumping it into a data lake, and building an API to extract needed information isn’t working. Click to learn more about author Brian Platz.

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Alation

JANUARY 26, 2023

Many users struggle to access the information they need or understand its full context once that access is unlocked. What’s worse, just 3% of the data in a business enterprise meets quality standards. There’s also no denying that data management is becoming more important, especially to the public.

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Alation

FEBRUARY 17, 2023

This past week, I had the pleasure of hosting Data Governance for Dummies author Jonathan Reichental for a fireside chat , along with Denise Swanson , Data Governance lead at Alation. Can you have proper data management without establishing a formal data governance program?

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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.

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Dataconomy

SEPTEMBER 4, 2023

Cloud analytics is the art and science of mining insights from data stored in cloud-based platforms. By tapping into the power of cloud technology, organizations can efficiently analyze large datasets, uncover hidden patterns, predict future trends, and make informed decisions to drive their businesses forward.

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Dataversity

OCTOBER 4, 2022

The rise of data lakes and adjacent patterns such as the data lakehouse has given data teams increased agility and the ability to leverage major amounts of data. Constantly evolving data privacy legislation and the impact of major cybersecurity breaches has led to the call for responsible data […].

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phData

NOVEMBER 9, 2023

The main goal of a data mesh structure is to drive: Domain-driven ownership Data as a product Self-service infrastructure Federated governance One of the primary challenges that organizations face is data governance. What is a Data Lake? Today, data lakes and data warehouses are colliding.

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Alation

FEBRUARY 1, 2022

A new research report by Ventana Research, Embracing Modern Data Governance , shows that modern data governance programs can drive a significantly higher ROI in a much shorter time span. Historically, data governance has been a manual and restrictive process, making it almost impossible for these programs to succeed.

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Alation

APRIL 6, 2023

Data governance is traditionally applied to structured data assets that are most often found in databases and information systems. This blog focuses on governing spreadsheets that contain data, information, and metadata, and must themselves be governed.

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AWS Machine Learning Blog

JUNE 5, 2023

Many teams are turning to Athena to enable interactive querying and analyze their data in the respective data stores without creating multiple data copies. Athena allows applications to use standard SQL to query massive amounts of data on an S3 data lake. Create a data lake with Lake Formation.

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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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IBM Journey to AI blog

AUGUST 4, 2023

It also requires an organization-wide data governance approach, from adopting new types of employee training to creating new policies for data storage. Architecture for data democratization Data democratization requires a move away from traditional “data at rest” architecture, which is meant for storing static data.

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Pickl AI

DECEMBER 2, 2024

This explosive growth of data is driven by various factors, including the proliferation of internet-connected devices, social media interactions, and the increasing digitization of business processes. Key Takeaways Big Data originates from diverse sources, including IoT and social media. What is Big Data?

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Pickl AI

NOVEMBER 25, 2024

This explosive growth of data is driven by various factors, including the proliferation of internet-connected devices, social media interactions, and the increasing digitization of business processes. Key Takeaways Big Data originates from diverse sources, including IoT and social media. What is Big Data?

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Dataversity

DECEMBER 16, 2020

According to IDC, the size of the global datasphere is projected to reach 163 ZB by 2025, leading to the disparate data sources in legacy systems, new system deployments, and the creation of data lakes and data warehouses. Most organizations do not utilize the entirety of the data […].

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IBM Journey to AI blog

OCTOBER 12, 2023

Accounting for the complexities of the AI lifecycle Unfortunately, typical data storage and data governance tools fall short in the AI arena when it comes to helping an organization perform the tasks that underline efficient and responsible AI lifecycle management. But the implementation of AI is only one piece of the puzzle.

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Dataversity

JULY 25, 2024

Over the past few years, the industry has increasingly recognized the need to adopt a data lakehouse architecture because of the inherent benefits. This approach improves data infrastructure costs and reduces time-to-insight by consolidating more data workloads into a single source of truth on the organization’s data lake.

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Alation

JUNE 9, 2021

In this four-part blog series on data culture, we’re exploring what a data culture is and the benefits of building one, and then drilling down to explore each of the three pillars of data culture – data search & discovery, data literacy, and data governance – in more depth. what does it look like?

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Dataconomy

FEBRUARY 23, 2023

They are responsible for designing, building, and maintaining the infrastructure and tools needed to manage and process large volumes of data effectively. This involves working closely with data analysts and data scientists to ensure that data is stored, processed, and analyzed efficiently to derive insights that inform decision-making.

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Alation

MAY 16, 2023

Many organizations use data visualization to identify patterns or consumer trends and communicate findings to stakeholders better. Data Integration A data pipeline can be used to gather data from various disparate sources in one data store. Checking the data quality before and after the cleansing steps is critical.

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Dataversity

SEPTEMBER 12, 2022

The ways in which we store and manage data have grown exponentially over recent years – and continue to evolve into new paradigms. For much of IT history, though, enterprise data architecture has existed as monolithic, centralized “data lakes.” The post Data Mesh or Data Mess?

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DataRobot Blog

OCTOBER 3, 2017

Many announcements at Strata centered on product integrations, with vendors closing the loop and turning tools into solutions, most notably: A Paxata-HDInsight solution demo, where Paxata showcased the general availability of its Adaptive Information Platform for Microsoft Azure.

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Dataversity

FEBRUARY 10, 2023

For many of these organizations, the path toward becoming more data-driven lies in the power of data lakehouses, which combine elements of data warehouse architecture with data lakes.

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Alation

FEBRUARY 13, 2020

A Data Catalog is 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. What is a Data Catalog?

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Alation

APRIL 19, 2022

And in an increasingly remote workforce, people need to access data systems easily to do their jobs. Today, data dwells everywhere. Data modernization enables informed decision making by pulling data out of systems more reliably. It helps you identify high-value data combinations and integrations.

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Precisely

OCTOBER 16, 2023

The cloud is especially well-suited to large-scale storage and big data analytics, due in part to its capacity to handle intensive computing requirements at scale. BI platforms and data warehouses have been replaced by modern data lakes and cloud analytics solutions.

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Precisely

JULY 18, 2024

While data fabric is not a standalone solution, critical capabilities that you can address today to prepare for a data fabric include automated data integration, metadata management, centralized data governance, and self-service access by consumers. Increase metadata maturity.

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Tableau

FEBRUARY 14, 2022

The data lakehouse is one such architecture—with “lake” from data lake and “house” from data warehouse. This modern, cloud-based data stack enables you to have all your data in one place while unlocking both backward-looking, historical analysis as well as forward-looking scenario planning and predictive analysis.

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