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 Science Blog

MARCH 14, 2023

Big Data tauchte als Buzzword meiner Recherche nach erstmals um das Jahr 2011 relevant in den Medien auf. Big Data wurde zum Business-Sprech der darauffolgenden Jahre. In der Parallelwelt der ITler wurde das Tool und Ökosystem Apache Hadoop quasi mit Big Data beinahe synonym gesetzt.

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Dataconomy

FEBRUARY 21, 2020

High quality, reliable data forms the backbone for all successful data endeavors, from reporting and analytics to machine learning. Delta Lake is an open-source storage layer that solves many concerns around data. The post How to make data lakes reliable appeared first on Dataconomy.

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databricks

JUNE 6, 2023

Apache Parquet is one of the most popular open source file formats in the big data world today. Being column-oriented, Apache Parquet allows.

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Precisely

MARCH 9, 2023

Data warehouse vs. data lake, each has their own unique advantages and disadvantages; it’s helpful to understand their similarities and differences. In this article, we’ll focus on a data lake vs. data warehouse. It is often used as a foundation for enterprise data lakes.

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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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Smart Data Collective

AUGUST 28, 2021

Data lakes and data warehouses are probably the two most widely used structures for storing data. Data Warehouses and Data Lakes in a Nutshell. A data warehouse is used as a central storage space for large amounts of structured data coming from various sources. Data Type and Processing.

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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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ODSC - Open Data Science

SEPTEMBER 29, 2023

But, the amount of data companies must manage is growing at a staggering rate. Research analyst firm Statista forecasts global data creation will hit 180 zettabytes by 2025. One way to address this is to implement a data lake: a large and complex database of diverse datasets all stored in their original format.

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The Data Administration Newsletter

JANUARY 3, 2023

For a while now, vendors have been advocating that people put their data in a data lake when they put their data in the cloud. The Data Lake The idea is that you put your data into a data lake. Then, at a later point in time, the end user analyst can come along and […].

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insideBIGDATA

APRIL 22, 2024

In this contributed article, Sida Shen, product marketing manager, CelerData, discusses how data lakehouse architectures promise the combined strengths of data lakes and data warehouses, but one question arises: why do we still find the need to transfer data from these lakehouses to proprietary data warehouses?

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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.

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Dataconomy

JULY 23, 2018

Since data has been called the “oil” of the new economy, it’s easy to assume that more is better. You can never have too much oil, so the same goes for data too, right? Hence there has been a lot of hype about data lakes over the past few years.

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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.

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Dataconomy

NOVEMBER 1, 2017

Anderson, Talend Regional Manager, Customer Success Architect & Kent Graziano, Snowflake Senior Technical Evangelist So you want to build a Data Lake? Perhaps you think a Data Lake will eliminate the need for a Data Warehouse and all your business users will merely. Ok, sure let’s talk about that.

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ODSC - Open Data Science

JUNE 1, 2023

Real-Time ML with Spark and SBERT, AI Coding Assistants, Data Lake Vendors, and ODSC East Highlights Getting Up to Speed on Real-Time Machine Learning with Spark and SBERT Learn more about real-time machine learning by using this approach that uses Apache Spark and SBERT. Well, these libraries will give you a solid start.

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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. Proper Scalability. Uses Powerful Algorithms.

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Flipboard

APRIL 17, 2023

Enterprises often rely on data warehouses and data lakes to handle big data for various purposes, from business intelligence to data science. A new approach, called a data lakehouse, aims to … But these architectures have limitations and tradeoffs that make them less than ideal for modern teams.

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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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Analytics Vidhya

FEBRUARY 27, 2023

Introduction Enterprises here and now catalyze vast quantities of data, which can be a high-end source of business intelligence and insight when used appropriately. Delta Lake allows businesses to access and break new data down in real time.

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Data Science Blog

MAY 15, 2023

tl;dr Ein Data Lakehouse ist eine moderne Datenarchitektur, die die Vorteile eines Data Lake und eines Data Warehouse kombiniert. Die Definition eines Data Lakehouse Ein Data Lakehouse ist eine moderne Datenspeicher- und -verarbeitungsarchitektur, die die Vorteile von Data Lakes und Data Warehouses vereint.

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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.

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Adrian Bridgwater for Forbes

MARCH 27, 2023

The data lakehouse is a hybrid term used to denote some of the structures we would find in a more ordered data warehouse with the expansiveness and lower cost functionality of the data lake. But, finding our way around the data lakehouse, even with its defined edges and channels can still be tough.

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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.

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Data Science Dojo

JULY 6, 2023

It integrates seamlessly with other AWS services and supports various data integration and transformation workflows. Google BigQuery: Google BigQuery is a serverless, cloud-based data warehouse designed for big data analytics. It provides a scalable and fault-tolerant ecosystem for big data processing.

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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?

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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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Adrian Bridgwater for Forbes

FEBRUARY 16, 2023

Part of the universe of virtual data topologies, a data lakehouse combines the expansive and unstructured raw data reserves we find in the data lake (that place we use to ‘pour’ data into, often before we know what to do with it)… and the more structured and ordered world of the data warehouse.

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Smart Data Collective

OCTOBER 26, 2019

Having cost-effective off-site backup allows companies to focus more on their methodology for backing up data than the price of that method. Closer sites for data storage mean lower cost, but a higher risk to the company. Big Data Storage Concerns. Further sites may be less cost-effective but more secure. Conclusion.

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Women in Big Data

NOVEMBER 8, 2023

At the same time, she made substantial contributions as the Munich Chapter Co-Lead at Women in Big Data, significantly impacting the organization’s achievements. Our innovative approach combines data lakes and data warehouses into the Lakehouse architecture. Please tell us about your current work.

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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.

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Smart Data Collective

FEBRUARY 23, 2022

Traditional relational databases provide certain benefits, but they are not suitable to handle big and various data. That is when data lake products started gaining popularity, and since then, more companies introduced lake solutions as part of their data infrastructure. How to improve indexing.

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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.

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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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The Data Administration Newsletter

MARCH 15, 2022

In her groundbreaking article, How to Move Beyond a Monolithic Data Lake to a Distributed Data Mesh, Zhamak Dehghani made the case for building data mesh as the next generation of enterprise data platform architecture.

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Smart Data Collective

AUGUST 7, 2019

Big data has the power to transform any small business. One study found that 77% of small businesses don’t even have a big data strategy. If your company lacks a big data strategy, then you need to start developing one today. Using Big Data to Fix Your Biggest Problems as a Business Owner.

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Alation

FEBRUARY 13, 2020

A lot of people in our audience are looking at implementing data lakes or are in the middle of big data lake initiatives. I know in February of 2017 Munich Re launched their own innovative platform as a cornerstone for analytics that involved a big data lake and a data catalog.

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