Analytics, Big Data Analytics and Data Lakes

Data lakes vs. data warehouses: Decoding the data storage debate

Data Science Dojo

JANUARY 12, 2023

When it comes to data, there are two main types: data lakes and data warehouses. What is a data lake? An enormous amount of raw data is stored in its original format in a data lake until it is required for analytics applications. Which one is right for your business?

Data Lakes

Data Lakes Data Warehouse Hadoop Machine Learning

Differentiating Between Data Lakes and Data Warehouses

Smart Data Collective

SEPTEMBER 23, 2020

While there is a lot of discussion about the merits of data warehouses, not enough discussion centers around data lakes. We talked about enterprise data warehouses in the past, so let’s contrast them with data lakes. Both data warehouses and data lakes are used when storing big data.

Data Lakes

Data Lakes Data Warehouse Big Data Big Data

Beyond data: Cloud analytics mastery for business brilliance

Dataconomy

SEPTEMBER 4, 2023

The modern corporate world is more data-driven, and companies are always looking for new methods to make use of the vast data at their disposal. Cloud analytics is one example of a new technology that has changed the game. What is cloud analytics? How does cloud analytics work?

Analytics

Analytics Analytics Big Data Analytics Big Data Analytics

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Important Considerations When Migrating to a Data Lake

Smart Data Collective

MARCH 30, 2022

Azure Data Lake Storage Gen2 is based on Azure Blob storage and offers a suite of big data analytics features. If you don’t understand the concept, you might want to check out our previous article on the difference between data lakes and data warehouses. Determine your preparedness.

Data Lakes

Data Lakes Azure Big Data Analytics Big Data Analytics

Here’s Why Automation For Data Lakes Could Be Important

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 Lakes

Data Lakes Big Data Big Data Data Scientist

Essential data engineering tools for 2023: Empowering for management and analysis

Data Science Dojo

JULY 6, 2023

Google BigQuery: Google BigQuery is a serverless, cloud-based data warehouse designed for big data analytics. It offers scalable storage and compute resources, enabling data engineers to process large datasets efficiently. It supports batch processing and is widely used for data-intensive tasks.

Data Engineering

Data Engineering Data Engineering Data Engineer Data Engineering

Unstructured data management and governance using AWS AI/ML and analytics services

Flipboard

OCTOBER 25, 2023

Therefore, there is a need to being able to analyze and extract value from the data economically and flexibly. Solution overview Data and metadata discovery is one of the primary requirements in data analytics, where data consumers explore what data is available and in what format, and then consume or query it for analysis.

AWS

AWS ML ML Analytics

5 Best Practices for Extracting, Analyzing, and Visualizing Data

Smart Data Collective

DECEMBER 13, 2022

However, computerization in the digital age creates massive volumes of data, which has resulted in the formation of several industries, all of which rely on data and its ever-increasing relevance. Data analytics and visualization help with many such use cases. It is the time of big data.

Data Analysis

Data Analysis Data Analysis Analytics Analytics

10 Things AWS Can Do for Your SaaS Company

Smart Data Collective

FEBRUARY 20, 2022

Whether it’s data management, analytics, or scalability, AWS can be the top-notch solution for any SaaS company. Data storage databases. Your SaaS company can store and protect any amount of data using Amazon Simple Storage Service (S3), which is ideal for data lakes, cloud-native applications, and mobile apps.

AWS

AWS Cloud Computing Data Lakes Database

Big Data – Das Versprechen wurde eingelöst

Data Science Blog

MARCH 14, 2023

Von Data Science spricht auf Konferenzen heute kaum noch jemand und wurde hype-technisch komplett durch Machine Learning bzw. Big Data Analytics erreicht die nötige Reife Der Begriff Big Data war schon immer etwas schwammig und wurde von vielen Unternehmen und Experten schnell auch im Kontext kleinerer Datenmengen verwendet.

Big Data

Big Data Big Data Apache Hadoop Data Science

How Getir reduced model training durations by 90% with Amazon SageMaker and AWS Batch

AWS Machine Learning Blog

DECEMBER 4, 2023

We capitalized on the powerful tools provided by AWS to tackle this challenge and effectively navigate the complex field of machine learning (ML) and predictive analytics. This capability of predictive analytics, particularly the accurate forecast of product categories, has proven invaluable.

AWS

AWS Predictive Analytics ML ML

Unlock the power of data governance and no-code machine learning with Amazon SageMaker Canvas and Amazon DataZone

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.

Machine Learning

Machine Learning Machine Learning Data Governance ML

A Comprehensive Guide to the main components of Big Data

Pickl AI

DECEMBER 2, 2024

Summary: Big Data encompasses vast amounts of structured and unstructured data from various sources. Key components include data storage solutions, processing frameworks, analytics tools, and governance practices. Key Takeaways Big Data originates from diverse sources, including IoT and social media.

Big Data

Big Data Big Data Data Lakes Apache Hadoop

Apply fine-grained data access controls with AWS Lake Formation in Amazon SageMaker Data Wrangler

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.

AWS

AWS Data Lakes Clustering Data Preparation

Getir end-to-end workforce management: Amazon Forecast and AWS Step Functions

AWS Machine Learning Blog

DECEMBER 7, 2023

He joined Getir in 2019 and currently works as a Senior Data Science & Analytics Manager. His team is responsible for designing, implementing, and maintaining end-to-end machine learning algorithms and data-driven solutions for Getir. He then joined Getir in 2019 and currently works as Data Science & Analytics Manager.

AWS

AWS Algorithm Machine Learning Machine Learning

A Comprehensive Guide to the Main Components of Big Data

Pickl AI

NOVEMBER 25, 2024

Summary: Big Data encompasses vast amounts of structured and unstructured data from various sources. Key components include data storage solutions, processing frameworks, analytics tools, and governance practices. Key Takeaways Big Data originates from diverse sources, including IoT and social media.

Big Data

Big Data Big Data Data Lakes Apache Hadoop

Characteristics of Big Data: Types & 5 V’s of Big Data

Pickl AI

SEPTEMBER 17, 2024

The importance of Big Data lies in its potential to provide insights that can drive business decisions, enhance customer experiences, and optimise operations. Organisations can harness Big Data Analytics to identify trends, predict outcomes, and make informed decisions that were previously unattainable with smaller datasets.

Big Data

Big Data Big Data Big Data Analytics Big Data Analytics

Discover 3 Vital Signs Your Business is Ready for AI and Explosive Growth

Towards AI

FEBRUARY 21, 2023

To make this easier, businesses must create an organized data storage and retrieval system. Storage tools like data warehouses and data lakes will help efficiently store the data, streamlining both retrieval and analysis. The analysis helps to identify patterns and trends that can provide actionable insights.

Artificial Intelligence

Artificial Intelligence Artificial Intelligence AI AI

Big Data Syllabus: A Comprehensive Overview

Pickl AI

AUGUST 9, 2024

Summary: A comprehensive Big Data syllabus encompasses foundational concepts, essential technologies, data collection and storage methods, processing and analysis techniques, and visualisation strategies. Velocity It indicates the speed at which data is generated and processed, necessitating real-time analytics capabilities.

Big Data

Big Data Big Data Big Data Analytics Big Data Analytics

TDC Digital leverages IBM Cloud for transparent billing and improved customer satisfaction

IBM Journey to AI blog

MAY 19, 2023

With high-speed file transfer, integrated services and cross-region offerings, IBM Cloud Object Storage allows you to leverage your data securely. In addition, it helps to reduce backup costs, provide permanent access to archived data, store data for cloud-native applications and create data lakes for big data analytics and AI.

Big Data Analytics

Big Data Analytics Data Lakes Big Data Analytics Cloud Computing

Demand forecasting at Getir built with Amazon Forecast

AWS Machine Learning Blog

MAY 15, 2023

He joined Getir in 2019 and currently works as a Senior Data Science & Analytics Manager. His team is responsible for designing, implementing, and maintaining end-to-end machine learning algorithms and data-driven solutions for Getir. He then joined Getir in 2019 and currently works as Data Science & Analytics Manager.

Algorithm

Algorithm Data Scientist Machine Learning Machine Learning

Amazon SageMaker Feature Store now supports cross-account sharing, discovery, and access

AWS Machine Learning Blog

FEBRUARY 13, 2024

For example, the analytics team may curate features like customer profile, transaction history, and product catalogs in a central management account. The central feature store is located in a different account managed by data engineers and ML engineers, where the data governance layer and data lake are usually situated.

AWS

AWS ML ML Machine Learning

How Netflix Applies Big Data Across Business Verticals: Insights and Strategies

Pickl AI

SEPTEMBER 18, 2024

Introduction Netflix has transformed the entertainment landscape, not just through its vast library of content but also by leveraging Big Data across various business verticals. It utilises Amazon Web Services (AWS) as its main data lake, processing over 550 billion events daily—equivalent to approximately 1.3

Big Data

Big Data Big Data Apache Kafka Big Data Analytics

Azure Data Engineer Jobs

Pickl AI

APRIL 6, 2023

Data Engineering is one of the most productive job roles today because it imbibes both the skills required for software engineering and programming and advanced analytics needed by Data Scientists. How to Become an Azure Data Engineer? Data Warehousing concepts and knowledge should be strong. What is Polybase?

Azure

Azure Data Engineering Data Engineering Data Engineer

How to Effectively Handle Unstructured Data Using AI

DagsHub

NOVEMBER 11, 2024

Video : Movies, live streams, and CCTV footage combine visual and audio data, making them highly complex. Video analytics enable object detection, motion tracking, and behavioural analysis for security, traffic monitoring, or customer engagement insights.

AI

AI AI Data Lakes Database

Your Complete Roadmap to Become an Azure Data Scientist

Pickl AI

SEPTEMBER 5, 2024

Introduction Data Science is revolutionising industries by extracting valuable insights from complex data sets, driving innovation, and enhancing decision-making. This roadmap aims to guide aspiring Azure Data Scientists through the essential steps to build a successful career.

Azure

Azure Data Scientist Machine Learning Machine Learning

Unfolding the Details of Hive in Hadoop

Pickl AI

JULY 6, 2023

Suboptimal Performance for Complex Queries While Hive excels in processing simple queries, its performance may degrade when dealing with complex analytical queries that involve multiple joins and aggregations. How Data Flows in Hive In Hive, data flows through several steps to enable querying and analysis.

Hadoop

Hadoop SQL Big Data Big Data

Mainframe Data: Empowering Democratized Cloud Analytics

Precisely

OCTOBER 16, 2023

Rapid advancements in digital technologies are transforming cloud-based computing and cloud analytics. Big data analytics, IoT, AI, and machine learning are revolutionizing the way businesses create value and competitive advantage. In a connected mainframe/cloud environment, data is often diverse and fragmented.

Analytics

Analytics Analytics Big Data Analytics Big Data Analytics

Generative AI for agriculture: How Agmatix is improving agriculture with Amazon Bedrock

AWS Machine Learning Blog

NOVEMBER 12, 2024

Discoveries and improvements across seed genetics, site-specific fertilizers, and molecule development for crop protection products have coincided with innovations in generative AI , Internet of Things (IoT) and integrated research and development trial data, and high-performance computing analytical services.

AWS

AWS AI AI Data Lakes

Azure Data Engineer Portfolio Project Series For Beginners (Part-I)

Towards AI

NOVEMBER 15, 2024

As you can see on the left side of the above image, there are many services like AI + Machine Learning, Analytics, Compute, Containers, Databases, DevOps, Integration, Networking, Security, Storage, and many more categories of resources. Now you can see the Data storage option. In that, you choose any as per your requirement.

Azure

Azure Data Engineering Data Engineering Data Engineer

Data Science Current

Data lakes vs. data warehouses: Decoding the data storage debate

Differentiating Between Data Lakes and Data Warehouses

Webinars

Trending Sources

Beyond data: Cloud analytics mastery for business brilliance

Webinars

Important Considerations When Migrating to a Data Lake

Here’s Why Automation For Data Lakes Could Be Important

Essential data engineering tools for 2023: Empowering for management and analysis

Unstructured data management and governance using AWS AI/ML and analytics services

5 Best Practices for Extracting, Analyzing, and Visualizing Data

10 Things AWS Can Do for Your SaaS Company

Big Data – Das Versprechen wurde eingelöst

How Getir reduced model training durations by 90% with Amazon SageMaker and AWS Batch

Unlock the power of data governance and no-code machine learning with Amazon SageMaker Canvas and Amazon DataZone

A Comprehensive Guide to the main components of Big Data

Apply fine-grained data access controls with AWS Lake Formation in Amazon SageMaker Data Wrangler

Getir end-to-end workforce management: Amazon Forecast and AWS Step Functions

A Comprehensive Guide to the Main Components of Big Data

Characteristics of Big Data: Types & 5 V’s of Big Data

Discover 3 Vital Signs Your Business is Ready for AI and Explosive Growth

Big Data Syllabus: A Comprehensive Overview

TDC Digital leverages IBM Cloud for transparent billing and improved customer satisfaction

Demand forecasting at Getir built with Amazon Forecast

Amazon SageMaker Feature Store now supports cross-account sharing, discovery, and access

How Netflix Applies Big Data Across Business Verticals: Insights and Strategies

Azure Data Engineer Jobs

How to Effectively Handle Unstructured Data Using AI

Your Complete Roadmap to Become an Azure Data Scientist

Unfolding the Details of Hive in Hadoop

Mainframe Data: Empowering Democratized Cloud Analytics

Generative AI for agriculture: How Agmatix is improving agriculture with Amazon Bedrock

Azure Data Engineer Portfolio Project Series For Beginners (Part-I)

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