insideBIGDATA

AUGUST 28, 2024

Dremio, the unified lakehouse platform for self-service analytics and AI, announced a breakthrough in data lake analytics performance capabilities, extending its leadership in self-optimizing, autonomous Iceberg data management.

Analytics 261

Analytics Analytics Data Lakes AI 261

Analytics Vidhya

JANUARY 2, 2023

Introduction Delta Lake is an open-source storage layer that brings data lakes to the world of Apache Spark. Delta Lakes provides an ACID transaction–compliant and cloud–native platform on top of cloud object stores such as Amazon S3, Microsoft Azure Storage, and Google Cloud Storage.

Data Lakes 336

Data Lakes Azure Analytics Analytics 336

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.

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Data Lakes Data Warehouse Big Data Big Data 135

Analytics Vidhya

FEBRUARY 27, 2023

Delta Lake allows businesses to access and break new data down in real time. Delta Lake is an open-source warehouse layer designed to run on top of data lakes analogous to […] The post A Comprehensive Guide on Delta Lake appeared first on Analytics Vidhya.

Data Lakes 315

Data Lakes Business Intelligence Business Intelligence Analytics 315

Flipboard

NOVEMBER 22, 2024

It enables different business units within an organization to create, share, and govern their own data assets, promoting self-service analytics and reducing the time required to convert data experiments into production-ready applications. We discuss this in more detail later in this post.

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Data Governance ML ML Data Lakes 132

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 106

Data Lakes Big Data Big Data Data Scientist 106

Pickl AI

APRIL 21, 2025

Summary: Big Data refers to the vast volumes of structured and unstructured data generated at high speed, requiring specialized tools for storage and processing. Data Science, on the other hand, uses scientific methods and algorithms to analyses this data, extract insights, and inform decisions.

Big Data 52

Big Data Big Data Data Science Machine Learning 52

Smart Data Collective

APRIL 24, 2020

Perhaps one of the biggest perks is scalability, which simply means that with good data lake ingestion a small business can begin to handle bigger data numbers. The reality is businesses that are collecting data will likely be doing so on several levels. Data Analytics Simplified. Proper Scalability.

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Data Lakes Algorithm Deep Learning Deep Learning 131

Dataconomy

APRIL 13, 2021

Data professionals have long debated the merits of the data lake versus the data warehouse. But this debate has become increasingly intense in recent times with the prevalence of data and analytics workloads in the cloud, the growing frustration with the brittleness of Hadoop, and hype around a new architectural.

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Data Lakes Data Warehouse Hadoop Analytics 237

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.

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Data Lakes Azure Big Data Analytics Big Data Analytics 116

Precisely

JANUARY 9, 2025

Data marts soon evolved as a core part of a DW architecture to eliminate this noise. Data marts involved the creation of built-for-purpose analytic repositories meant to directly support more specific business users and reporting needs (e.g., financial reporting, customer analytics, supply chain management). A data lake!

Data Warehouse 119

Data Warehouse Hadoop Data Governance Data Lakes 119

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 203

Analytics Analytics Big Data Analytics Big Data Analytics 203

Dataconomy

FEBRUARY 25, 2025

Big data, when properly harnessed, moves beyond mere data accumulation, offering a lens through which future trends and actionable insights can be precisely forecast. What is big data? Big data has become a crucial component of modern business strategy, transforming how organizations operate and make decisions.

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Big Data Big Data Data Lakes Machine Learning 91

ODSC - Open Data Science

SEPTEMBER 27, 2023

In the ever-evolving world of big data, managing vast amounts of information efficiently has become a critical challenge for businesses across the globe. Understanding Data Lakes A data lake is a centralized repository that stores structured, semi-structured, and unstructured data in its raw format.

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Data Lakes Data Warehouse Database Big Data 98

Smart Data Collective

AUGUST 9, 2019

Big data in the gaming industry has played a phenomenal role in the field. We have previously talked about the benefits of using big data by gaming providers that offer cash games, such as slots. However, more mainstream games use big data as well. Big Data is the Lynchpin of the Fortnite Gaming Experience.

Big Data 96

Big Data Big Data Data Lakes Machine Learning 96

Dataconomy

DECEMBER 24, 2021

For decades, managing data essentially meant collecting, storing, and occasionally accessing it. That has all changed in recent years, as businesses look for the critical information that can be pulled from the massive amounts of data being generated, accessed, and stored in myriad locations, from corporate data centers to the cloud.

Analytics 242

Analytics Analytics Data Lakes Big Data 242

Dataversity

AUGUST 27, 2021

If this time 10 years ago you were working in data and analytics, something was about to happen that would go on to dominate a large part of your professional life. I’m talking about the emergence of “big data.” The post Big Data at 10: Did Bigger Mean Better? appeared first on DATAVERSITY.

Big Data 98

Big Data Big Data Analytics Analytics 98

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 provides a scalable and fault-tolerant ecosystem for big data processing.

Data Engineer 195

Data Engineer Data Engineering Data Engineering Data Engineering 195

IBM Journey to AI blog

JULY 5, 2023

Data Lakes have been around for well over a decade now, supporting the analytic operations of some of the largest world corporations. Such data volumes are not easy to move, migrate or modernize. The challenges of a monolithic data lake architecture Data lakes are, at a high level, single repositories of data at scale.

Data Lakes 78

Data Lakes Data Warehouse Data Governance Analytics 78

Alation

AUGUST 4, 2022

It’s been one decade since the “ Big Data Era ” began (and to much acclaim!). Analysts asked, What if we could manage massive volumes and varieties of data? Yet the question remains: How much value have organizations derived from big data? Big Data as an Enabler of Digital Transformation.

Big Data 95

Big Data Big Data Apache Kafka Data Lakes 95

Dataconomy

JUNE 1, 2023

Microsoft has made good on its promise to deliver a simplified and more efficient Microsoft Fabric price model for its end-to-end platform designed for analytics and data workloads. Microsoft’s unified pricing model for the Fabric suite marks a significant advancement in the analytics and data market.

Power BI 194

Power BI Data Lakes Azure Data Silos 194

Precisely

MARCH 9, 2023

As cloud computing platforms make it possible to perform advanced analytics on ever larger and more diverse data sets, new and innovative approaches have emerged for storing, preprocessing, and analyzing information. In this article, we’ll focus on a data lake vs. data warehouse.

Data Warehouse 59

Data Warehouse Data Lakes Hadoop Big Data 59

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 167

AWS ML ML Analytics 167

insideBIGDATA

FEBRUARY 2, 2024

In this contributed article, Tom Scott, CEO of Streambased, outlines the path event streaming systems have taken to arrive at the point where they must adopt analytical use cases and looks at some possible futures in this area.

Analytics 363

Analytics Analytics Data Lakes Big Data 363

Dataconomy

FEBRUARY 23, 2023

Data engineers play a crucial role in managing and processing big data. They are responsible for designing, building, and maintaining the infrastructure and tools needed to manage and process large volumes of data effectively. They must also ensure that data privacy regulations, such as GDPR and CCPA , are followed.

Big Data 91

Big Data Big Data Data Engineer Data Engineering 91

Flipboard

DECEMBER 11, 2024

Many of these applications are complex to build because they require collaboration across teams and the integration of data, tools, and services. Data engineers use data warehouses, data lakes, and analytics tools to load, transform, clean, and aggregate data.

SQL 160

SQL AWS Data Lakes AI 160

Women in Big Data

OCTOBER 9, 2024

With the explosive growth of big data over the past decade and the daily surge in data volumes, it’s essential to have a resilient system to manage the vast influx of information without failures. The success of any data initiative hinges on the robustness and flexibility of its big data pipeline.

Big Data 59

Big Data Big Data Apache Kafka Data Pipeline 59

Pickl AI

SEPTEMBER 17, 2024

Summary: This blog delves into the multifaceted world of Big Data, covering its defining characteristics beyond the 5 V’s, essential technologies and tools for management, real-world applications across industries, challenges organisations face, and future trends shaping the landscape.

Big Data 52

Big Data Big Data Big Data Analytics Big Data Analytics 52

Analytics Vidhya

MARCH 5, 2023

HDInsight works seamlessly with the Hadoop ecosystem, which includes technologies like MapReduce, Hive, […] The post Top 6 Microsoft HDFS Interview Questions appeared first on Analytics Vidhya.

Hadoop 319

Hadoop Azure Analytics Analytics 319

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.

Data Lakes 59

Data Lakes Data Warehouse Data Quality Data Governance 59

Women in Big Data

NOVEMBER 27, 2024

By maintaining historical data from disparate locations, a data warehouse creates a foundation for trend analysis and strategic decision-making. How to Choose a Data Warehouse for Your Big Data Choosing a data warehouse for big data storage necessitates a thorough assessment of your unique requirements.

Data Warehouse 59

Data Warehouse Big Data Big Data Azure 59

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 52

Big Data Big Data Data Lakes Apache Hadoop 52

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 52

Big Data Big Data Data Lakes Apache Hadoop 52

Alation

FEBRUARY 20, 2020

Architecturally the introduction of Hadoop, a file system designed to store massive amounts of data, radically affected the cost model of data. Organizationally the innovation of self-service analytics, pioneered by Tableau and Qlik, fundamentally transformed the user model for data analysis. The Rise of the Data Catalog.

Data Lakes 52

Data Lakes Hadoop Tableau Big Data 52

Tableau

JUNE 8, 2021

In many of the conversations we have with IT and business leaders, there is a sense of frustration about the speed of time-to-value for big data and data science projects. We often hear that organizations have invested in data science capabilities but are struggling to operationalize their machine learning models.

Tableau 102

Tableau Data Lakes Data Warehouse SQL 102

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.

Data Lakes 52

Data Lakes Data Warehouse Database ETL 52

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. Fundamentals of Big Data Understanding the fundamentals of Big Data is crucial for anyone entering this field.

Big Data 52

Big Data Big Data Big Data Analytics Big Data Analytics 52