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.

Data Lakes 52

Data Lakes Hadoop Tableau Big Data 52

Dataconomy

MARCH 4, 2025

Each stage is crucial for deriving meaningful insights from data. Data gathering The first step is gathering relevant data from various sources. This could include data warehouses, data lakes, or even external datasets.

Data Mining 91

Data Mining Data Mining Data Mining Decision Trees 91

The MLOps Blog

MARCH 21, 2023

Your data scientists develop models on this component, which stores all parameters, feature definitions, artifacts, and other experiment-related information they care about for every experiment they run. Machine Learning Operations (MLOps): Overview, Definition, and Architecture (by Kreuzberger, et al., AIIA MLOps blueprints.

Machine Learning 69

Machine Learning Machine Learning Data Scientist ML 69

phData

NOVEMBER 9, 2023

A data warehouse is a centralized and structured storage system that enables organizations to efficiently store, manage, and analyze large volumes of data for business intelligence and reporting purposes. What is a Data Lake? What is the Difference Between a Data Lake and a Data Warehouse?

Data Warehouse 98

Data Warehouse Data Lakes Clustering Cloud Data 98

Flipboard

NOVEMBER 17, 2023

The vector field should be represented as an array of numbers (BSON int32, int64, or double data types only). Query the vector data store You can query the vector data store using the Vector Search aggregation pipeline. It uses the Vector Search index and performs a semantic search on the vector data store.

K-nearest Neighbors 169

K-nearest Neighbors AWS Clustering Database 169

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. New insights and relationships are found in this combination. All of this supports the use of AI.

Data Lakes 95

Data Lakes Data Warehouse AI AI 95

Alation

JANUARY 13, 2022

Thoughtworks says data mesh is key to moving beyond a monolithic data lake. Spoiler alert: data fabric and data mesh are independent design concepts that are, in fact, quite complementary. Thoughtworks says data mesh is key to moving beyond a monolithic data lake 2. Gartner on Data Fabric.

Data Lakes 59

Data Lakes Data Governance Data Quality Data Warehouse 59

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 Data Lakes Clustering Data Preparation 98

AWS Machine Learning Blog

SEPTEMBER 1, 2023

These teams are as follows: Advanced analytics team (data lake and data mesh) – Data engineers are responsible for preparing and ingesting data from multiple sources, building ETL (extract, transform, and load) pipelines to curate and catalog the data, and prepare the necessary historical data for the ML use cases.

AI 126

AI AI ML ML 126

Alation

NOVEMBER 18, 2021

External Tables Create a Shared View of the Data Lake. We’ve seen external tables become popular with our customers, who use them to provide a normalized relational schema on top of their data lake. Essentially, external tables create a shared view of the data lake, a single pane of glass everyone can reference.

Data Lakes 52

Data Lakes Data Governance SQL AWS 52

Mlearning.ai

JUNE 19, 2023

How they can supplement Data Lakes and Data Warehouses medium.com The news are also quite fitting, since Google will now enter a partnership with Tumult Labs, a leader in differential privacy for companies and government agencies[4].

Data Lakes 52

Data Lakes Data Warehouse SQL ML 52

IBM Journey to AI blog

JANUARY 18, 2023

In another decade, the internet and mobile started the generate data of unforeseen volume, variety and velocity. It required a different data platform solution. Hence, Data Lake emerged, which handles unstructured and structured data with huge volume. It is narrower in focus than data fabric.

Data Lakes 52

Data Lakes Data Warehouse Azure Apache Hadoop 52

Flipboard

AUGUST 17, 2023

Amazon Redshift uses SQL to analyze structured and semi-structured data across data warehouses, operational databases, and data lakes, using AWS-designed hardware and ML to deliver the best price-performance at any scale. If you want to do the process in a low-code/no-code way, you can follow option C.

ML 123

ML ML AWS Data Warehouse 123

Tableau

APRIL 18, 2022

Ensure the behaves the way you want it to— especially sensitive data and access. Data integration. Gain useful insights from data stored across different platforms and data sources, such as data warehouses, data lakes, and CRMs. Create trust and verifiability where viewers consume their data.

Tableau 102

Tableau Data Quality Analytics Analytics 102

Tableau

APRIL 18, 2022

Ensure the behaves the way you want it to— especially sensitive data and access. Data integration. Gain useful insights from data stored across different platforms and data sources, such as data warehouses, data lakes, and CRMs. Create trust and verifiability where viewers consume their data.

Tableau 98

Tableau Data Quality Analytics Analytics 98

ODSC - Open Data Science

FEBRUARY 2, 2023

To get a better grip on those changes we reviewed over 25,000 data scientist job descriptions from that past year to find out what employers are looking for in 2023. Much of what we found was to be expected, though there were definitely a few surprises. You’ll see specific tools in the next section.

Data Science 98

Data Science Data Scientist Computer Science Computer Science 98

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. Conclusion.

Data Lakes 64

Data Lakes Data Analysis Data Analysis Big Data 64

AWS Machine Learning Blog

JANUARY 13, 2023

Amazon Simple Storage Service (Amazon S3) object storage acts as a content data lake. TR built processes to securely access data from the content data lake to users’ experimentation workspaces while maintaining required authorization and auditability.

ML 98

ML ML AWS Data Scientist 98

O'Reilly Media

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.

ML 145

ML ML Data Scientist AWS 145

Alation

JUNE 14, 2021

Guided Navigation Guided navigation helps data stewards locate sensitive data. This includes finding the most exposed sensitive data and ensuring it is used properly. There are many locations where sensitive data can reside — from data lakes, databases, and reports, to APIs and queries.

Data Governance 97

Data Governance Data Lakes Data Classification Data Quality 97

Alation

FEBRUARY 17, 2023

Reichental describes data governance as the overarching layer that empowers people to manage data well ; as such, it is focused on roles & responsibilities, policies, definitions, metrics, and the lifecycle of the data. In this way, data governance is the business or process side. This is a very good thing.

Data Governance 52

Data Governance Data Quality Data Analyst Data Pipeline 52

IBM Journey to AI blog

JULY 1, 2024

The first two use cases are primarily aimed at a technical audience, as the lineage definitions apply to actual physical assets. Data is touched and manipulated by a myriad of solutions, including on-premises and cloud transformation tools, databases and data lake houses.

ETL 40

ETL Data Lakes Database Data Pipeline 40

Alation

AUGUST 11, 2022

Today, the brightest minds in our industry are targeting the massive proliferation of data volumes and the accompanying but hard-to-find value locked within all that data. A modern data stack gives a neat, closed-loop definition of what is needed. But “customer” is an easy one. It could be gross margin.

Data Warehouse 52

Data Warehouse Data Engineering Data Engineering Data Engineer 52

AWS Machine Learning Blog

JUNE 25, 2024

The customer review analysis workflow consists of the following steps: A user uploads a file to dedicated data repository within your Amazon Simple Storage Service (Amazon S3) data lake, invoking the processing using AWS Step Functions. The definition of our end-to-end orchestration is detailed in the GitHub repo.

AWS 126

AWS Natural Language Processing Machine Learning Machine Learning 126

Alation

JANUARY 10, 2023

The value of a data catalog means something different to each of these companies — meaning they will each expect something different out of its implementation. In fact, they likely have different definitions of what a data catalog even is. How do you define a data catalog? How do you derive value from a data catalog?

Data Lakes 52

Data Lakes Data Analyst Analytics Analytics 52

DagsHub

OCTOBER 23, 2024

Here are some challenges you might face while managing unstructured data: Storage consumption: Unstructured data can consume a large volume of storage. For instance, if you are working with several high-definition videos, storing them would take a lot of storage space, which could be costly.

Machine Learning 52

Machine Learning Machine Learning Data Lakes AI 52

AWS Machine Learning Blog

JUNE 13, 2023

The combination of large language models (LLMs), including the ease of integration that Amazon Bedrock offers, and a scalable, domain-oriented data infrastructure positions this as an intelligent method of tapping into the abundant information held in various analytics databases and data lakes.

Database 100

Database SQL AWS AI 100

Alation

APRIL 18, 2023

For any data user in an enterprise today, data profiling is a key tool for resolving data quality issues and building new data solutions. In this blog, we’ll cover the definition of data profiling, top use cases, and share important techniques and best practices for data profiling today.

Data Profiling 52

Data Profiling Data Quality Data Governance Data Pipeline 52

ODSC - Open Data Science

NOVEMBER 18, 2024

You’ll start by demystifying what vector databases are, with clear definitions, simple explanations, and real-world examples of popular vector databases. You will also gain a practical understanding of how vector databases work, including the processes involved in storing, retrieving, and managing data in high-dimensional vector spaces.

Deep Learning 40

Deep Learning Deep Learning Database Data Science 40

AWS Machine Learning Blog

JUNE 22, 2023

In LnW Connect, an encryption process was designed to provide a secure and reliable mechanism for the data to be brought into an AWS data lake for predictive modeling. Dataset Slot machine environments are highly regulated and are deployed in an air-gapped environment.

AWS 111

AWS ML ML Machine Learning 111

Pickl AI

AUGUST 1, 2023

Key Components of Data Engineering Data Ingestion : Gathering data from various sources, such as databases, APIs, files, and streaming platforms, and bringing it into the data infrastructure. Data Processing: Performing computations, aggregations, and other data operations to generate valuable insights from the data.

Data Engineering 52

Data Engineering Data Engineer Data Engineering Data Engineering 52

ODSC - Open Data Science

JUNE 12, 2023

This article is an excerpt from the book Expert Data Modeling with Power BI, Third Edition by Soheil Bakhshi, a completely updated and revised edition of the bestselling guide to Power BI and data modeling. A quick search on the Internet provides multiple definitions by technology-leading companies such as IBM, Amazon, and Oracle.

Power BI 52

Power BI Data Warehouse ETL Data Preparation 52

AWS Machine Learning Blog

NOVEMBER 22, 2023

This culture is sustained by clear SLAs that set definitive expectations for processing times and accuracy, ensuring all team members are oriented towards common goals. By centralizing datasets within the flywheel’s dedicated Amazon S3 data lake, you ensure efficient data management.

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AWS ML ML Machine Learning 118

AWS Machine Learning Blog

AUGUST 26, 2024

You can integrate existing data from AWS data lakes, Amazon Simple Storage Service (Amazon S3) buckets, or Amazon Relational Database Service (Amazon RDS) instances with services such as Amazon Bedrock and Amazon Q. Role context – Start each prompt with a clear role definition.

AWS 128

AWS AI AI K-nearest Neighbors 128

phData

MAY 6, 2024

Now, a single customer might use multiple emails or phone numbers, but matching in this way provides a precise definition that could significantly reduce or even eliminate the risk of accidentally associating the actions of multiple customers with one identity. Store this data in a customer data platform or data lake.

Data Lakes 52

Data Lakes Data Warehouse Cloud Data SQL 52

Alation

APRIL 14, 2022

For example, data science always consumes “historical” data, and there is no guarantee that the semantics of older datasets are the same, even if their names are unchanged. Pushing data to a data lake and assuming it is ready for use is shortsighted. It’s not a simple definition.

Data Governance 59

Data Governance ML ML Cloud Data 59

Alation

MARCH 21, 2023

Having been in business for over 50 years, ARC had accumulated a massive amount of data that was stored in siloed, on-premises servers across its 7 business domains. Using Alation, ARC automated the data curation and cataloging process. “So

Analytics 52

Analytics Analytics Data Silos Big Data 52