Analytics Vidhya

DECEMBER 1, 2021

Components of Data Engineering Object Storage Object Storage MinIO Install Object Storage MinIO Data Lake with Buckets Demo Data Lake Management Conclusion References What is Data Engineering? The post How to Implement Data Engineering in Practice? appeared first on Analytics Vidhya.

Data Lake 391

Data Lake Data Science Publishing Software 391

AWS Big Data

DECEMBER 4, 2024

This week on the keynote stages at AWS re:Invent 2024, you heard from Matt Garman, CEO, AWS, and Swami Sivasubramanian, VP of AI and Data, AWS, speak about the next generation of Amazon SageMaker , the center for all of your data, analytics, and AI. The relationship between analytics and AI is rapidly evolving.

Data Analytics 101

Data Analytics Analytics Data Lake Data Quality 101

Analytics Vidhya

FEBRUARY 25, 2023

Introduction A data lake is a centralized and scalable repository storing structured and unstructured data. The need for a data lake arises from the growing volume, variety, and velocity of data companies need to manage and analyze.

Data Lake 179

Data Lake Unstructured Data Management Analytics 179

AWS Big Data

MARCH 13, 2025

At AWS re:Invent 2024, we announced the next generation of Amazon SageMaker , the center for all your data, analytics, and AI. It enables teams to securely find, prepare, and collaborate on data assets and build analytics and AI applications through a single experience, accelerating the path from data to value.

Analytics 87

Analytics Data Lake Data Warehouse Data-driven 87

Corinium

JUNE 6, 2019

Will you please describe your role at Fractal Analytics? Are you seeing currently any specific issues in the Insurance industry that should concern Chief Data & Analytics Officers? Are you seeing currently any specific issues in the Insurance industry that should concern Chief Data & Analytics Officers?

Analytics 250

Analytics Insurance Forecasting Deep Learning 250

David Menninger's Analyst Perspectives

OCTOBER 26, 2021

Databricks is a data engineering and analytics cloud platform built on top of Apache Spark that processes and transforms huge volumes of data and offers data exploration capabilities through machine learning models. The platform supports streaming data, SQL queries, graph processing and machine learning.

Big Data 327

Big Data Data Processing Machine Learning Modeling 327

AWS Big Data

JANUARY 15, 2025

For container terminal operators, data-driven decision-making and efficient data sharing are vital to optimizing operations and boosting supply chain efficiency. Enhance agility by localizing changes within business domains and clear data contracts. Eliminate centralized bottlenecks and complex data pipelines.

IoT 110

IoT Machine Learning Metadata Data-driven 110

AWS Big Data

DECEMBER 17, 2024

Amazon Redshift , launched in 2013, has undergone significant evolution since its inception, allowing customers to expand the horizons of data warehousing and SQL analytics. This allowed customers to scale read analytics workloads and offered isolation to help maintain SLAs for business-critical applications.

Data Lake 95

Data Lake Data Warehouse Data-driven Optimization 95

AWS Big Data

JUNE 10, 2024

This amalgamation empowers vendors with authority over a diverse range of workloads by virtue of owning the data. This authority extends across realms such as business intelligence, data engineering, and machine learning thus limiting the tools and capabilities that can be used.

Data Lake 126

Data Lake Metadata Snapshot Analytics 126

AWS Big Data

APRIL 3, 2024

They understand that a one-size-fits-all approach no longer works, and recognize the value in adopting scalable, flexible tools and open data formats to support interoperability in a modern data architecture to accelerate the delivery of new solutions.

Data Lake 121

Data Lake Snapshot Metadata Data Architecture 121

AWS Big Data

OCTOBER 29, 2024

The CDH is used to create, discover, and consume data products through a central metadata catalog, while enforcing permission policies and tightly integrating data engineering, analytics, and machine learning services to streamline the user journey from data to insight.

Data Lake 104

Data Lake Sales Metadata Machine Learning 104

AWS Big Data

DECEMBER 4, 2024

With this new functionality, customers can create up-to-date replicas of their data from applications such as Salesforce, ServiceNow, and Zendesk in an Amazon SageMaker Lakehouse and Amazon Redshift. SageMaker Lakehouse gives you the flexibility to access and query your data in-place with all Apache Iceberg compatible tools and engines.

Data Integration 112

Data Integration Data Lake Statistics Data-driven 112

AWS Big Data

NOVEMBER 26, 2024

Initially, data warehouses were the go-to solution for structured data and analytical workloads but were limited by proprietary storage formats and their inability to handle unstructured data. In practice, OTFs are used in a broad range of analytical workloads, from business intelligence to machine learning.

Metadata 105

Metadata Data Lake Snapshot Data Warehouse 105

David Menninger's Analyst Perspectives

JANUARY 22, 2021

Organizations are dealing with exponentially increasing data that ranges broadly from customer-generated information, financial transactions, edge-generated data and even operational IT server logs. A combination of complex data lake and data warehouse capabilities are required to leverage this data.

Data Lake 269

Data Lake IT Data Warehouse Data Governance 269

AWS Big Data

OCTOBER 1, 2024

Amazon Redshift enables you to efficiently query and retrieve structured and semi-structured data from open format files in Amazon S3 data lake without having to load the data into Amazon Redshift tables. Amazon Redshift extends SQL capabilities to your data lake, enabling you to run analytical queries.

Data Lake 115

Data Lake Statistics Broadcasting Optimization 115

AWS Big Data

JUNE 9, 2023

A modern data architecture enables companies to ingest virtually any type of data through automated pipelines into a data lake, which provides highly durable and cost-effective object storage at petabyte or exabyte scale.

Data Lake 130

Data Lake Metadata Statistics Optimization 130

AWS Big Data

JANUARY 6, 2025

Google Analytics 4 (GA4) provides valuable insights into user behavior across websites and apps. But what if you need to combine GA4 data with other sources or perform deeper analysis? It also helps you securely access your data in operational databases, data lakes, or third-party datasets with minimal movement or copying of data.

Analytics 98

Analytics Data Warehouse Metrics Big Data 98

AWS Big Data

JULY 20, 2023

With data becoming the driving force behind many industries today, having a modern data architecture is pivotal for organizations to be successful. In this post, we describe Orca’s journey building a transactional data lake using Amazon Simple Storage Service (Amazon S3), Apache Iceberg, and AWS Analytics.

Data Lake 98

Data Lake Analytics Snapshot Data Quality 98

AWS Big Data

SEPTEMBER 10, 2024

We often see requests from customers who have started their data journey by building data lakes on Microsoft Azure, to extend access to the data to AWS services. In such scenarios, data engineers face challenges in connecting and extracting data from storage containers on Microsoft Azure.

Data Lake 111

Data Lake Metadata Management Software 111

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.

Data Lake 122

Data Lake Sales Data Warehouse Snapshot 122

AWS Big Data

OCTOBER 9, 2023

Data lakes have been gaining popularity for storing vast amounts of data from diverse sources in a scalable and cost-effective way. As the number of data consumers grows, data lake administrators often need to implement fine-grained access controls for different user profiles.

Data Lake 131

Data Lake Testing Big Data Management 131

AWS Big Data

JULY 18, 2024

Over the years, organizations have invested in creating purpose-built, cloud-based data lakes that are siloed from one another. A major challenge is enabling cross-organization discovery and access to data across these multiple data lakes, each built on different technology stacks.

Data Lake 129

Data Lake Publishing Metadata Data-driven 129

David Menninger's Analyst Perspectives

SEPTEMBER 22, 2022

Organizations are collecting data from multiple data sources and a variety of systems to enrich their analytics and business intelligence (BI). But collecting data is only half of the equation. As the data grows, it becomes challenging to find the right data at the right time.

Data Lake 278

Data Lake Business Intelligence Analytics IT 278

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

AWS Big Data

DECEMBER 9, 2024

Given the importance of data in the world today, organizations face the dual challenges of managing large-scale, continuously incoming data while vetting its quality and reliability. One of its key features is the ability to manage data using branches. The data is visualized using matplotlib for interactive data analysis.

Data Quality 123

Data Quality Publishing Snapshot Data Lake 123

Jet Global

NOVEMBER 5, 2020

Option 3: Azure Data Lakes. This leads us to Microsoft’s apparent long-term strategy for D365 F&SCM reporting: Azure Data Lakes. Azure Data Lakes are highly complex and designed with a different fundamental purpose in mind than financial and operational reporting. Data lakes are not a mature technology.

Data Lake 98

Data Lake OLAP Data Warehouse Unstructured Data 98

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 112

Data Lake Metadata Data Warehouse Data Processing 112

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.

Data Lake 111

Data Lake Data Processing Metadata Snapshot 111

DataKitchen

NOVEMBER 29, 2021

As a result, enterprises will examine their end-to-end data operations and analytics creation workflows. Instead of allowing technology to be a barrier to teamwork, leading data organizations in 2022 will further expand the automation of workflows to improve and facilitate communication and coordination between the groups.

Testing 245

Testing Data Lake Data Architecture Manufacturing 245

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 116

Data Lake Analytics Data Warehouse Machine Learning 116

CIO Business Intelligence

DECEMBER 20, 2024

Beyond breaking down silos, modern data architectures need to provide interfaces that make it easy for users to consume data using tools fit for their jobs. Data must be able to freely move to and from data warehouses, data lakes, and data marts, and interfaces must make it easy for users to consume that data.

Data Architecture 122

Data Architecture Management Consulting Internet of Things 122

David Menninger's Analyst Perspectives

MARCH 17, 2021

Organizations are increasingly using data as a strategic asset, which makes data services critical. Huge volumes of data need to be stored, managed, discovered and analyzed. Cloud computing and storage approaches provide enterprises with various capabilities to store and process their data in third-party data centers.

Analytics 277

Analytics Enterprise Management Data Lake 277

AWS Big Data

NOVEMBER 29, 2023

This cloud service was a significant leap from the traditional data warehousing solutions, which were expensive, not elastic, and required significant expertise to tune and operate. Amazon Redshift Serverless, generally available since 2021, allows you to run and scale analytics without having to provision and manage the data warehouse.

Data Warehouse 127

Data Warehouse Analytics Data Lake Machine Learning 127

CIO Business Intelligence

MAY 12, 2022

What are predictive analytics tools? Predictive analytics tools blend artificial intelligence and business reporting. But there are deeper challenges because predictive analytics software can’t magically anticipate moments when the world shifts gears and the future bears little relationship to the past. Highlights. Deployment.

Predictive Analytics 137

Predictive Analytics Analytics Statistics Machine Learning 137

DataKitchen

AUGUST 3, 2021

First-generation – expensive, proprietary enterprise data warehouse and business intelligence platforms maintained by a specialized team drowning in technical debt. Second-generation – gigantic, complex data lake maintained by a specialized team drowning in technical debt. See the pattern? The problem is not “you.”

Data Architecture 246

Data Architecture Data Lake Cost-Benefit Data Warehouse 246

AWS Big Data

FEBRUARY 26, 2025

Analytics remained one of the key focus areas this year, with significant updates and innovations aimed at helping businesses harness their data more efficiently and accelerate insights. This zero-ETL integration reduces the complexity and operational burden of data replication to let you focus on deriving insights from your data.

Analytics 60

Analytics Data Lake Metadata Data Warehouse 60

David Menninger's Analyst Perspectives

JANUARY 14, 2021

But unlocking value from data requires multiple analytics workloads, data science tools and machine learning algorithms to run against the same diverse data sets.

Machine Learning 232

Machine Learning Data Governance Big Data Data Science 232