Monte Carlo

APRIL 24, 2023

Data lakes are useful, flexible data storage repositories that enable many types of data to be stored in its rawest state. Traditionally, after being stored in a data lake, raw data was then often moved to various destinations like a data warehouse for further processing, analysis, and consumption.

Data Lake 52

Data Lake Google Cloud Data Warehouse AWS 52

U-Next

SEPTEMBER 7, 2022

The terms “ Data Warehouse ” and “ Data Lake ” may have confused you, and you have some questions. Structuring data refers to converting unstructured data into tables and defining data types and relationships based on a schema. What is Data Lake? . Athena on AWS. .

Data Lake 52

Data Lake Data Warehouse Unstructured Data Amazon Web Services 52

DataKitchen

DECEMBER 9, 2024

They opted for Snowflake, a cloud-native data platform ideal for SQL-based analysis. The team landed the data in a Data Lake implemented with cloud storage buckets and then loaded into Snowflake, enabling fast access and smooth integrations with analytical tools.

Pharmaceutical 64

Pharmaceutical Data Lake Cloud Storage Project 64

Seattle Data Guy

FEBRUARY 10, 2024

Photo by Tiger Lily Data warehouses and data lakes play a crucial role for many businesses. It gives businesses access to the data from all of their various systems. As well as often integrating data so that end-users can answer business critical questions.

Data Lake 162

Data Lake Data Warehouse Data Accessibility 162

ProjectPro

AUGUST 11, 2021

“Data Lake vs Data Warehouse = Load First, Think Later vs Think First, Load Later” The terms data lake and data warehouse are frequently stumbled upon when it comes to storing large volumes of data. Data Warehouse Architecture What is a Data lake? What is a Data lake?

Data Lake 52

Data Lake Data Warehouse Cloud Hadoop 52

Cloudera

OCTOBER 23, 2024

In August, we wrote about how in a future where distributed data architectures are inevitable, unifying and managing operational and business metadata is critical to successfully maximizing the value of data, analytics, and AI.

Metadata 84

Metadata BI Data Lake Business Intelligence 84

Precisely

JUNE 24, 2024

A data leader from the manufacturing industry mentioned their need for a data mesh, but was still wrestling with a number of manual data management processes and needed to first focus on organizing their data into a local data warehouse or data lake.

Food 94

Food Data Analytics Pharmaceutical Consulting 94

Data Engineering Podcast

DECEMBER 25, 2022

Summary Encryption and security are critical elements in data analytics and machine learning applications. We have well developed protocols and practices around data that is at rest and in motion, but security around data in use is still severely lacking. or any other destination you choose. Pricing for SQLake is simple.

Machine Learning 130

Machine Learning Systems Data Lake Data Warehouse 130

Monte Carlo

AUGUST 25, 2023

That’s why it’s essential for teams to choose the right architecture for the storage layer of their data stack. But, the options for data storage are evolving quickly. Different vendors offering data warehouses, data lakes, and now data lakehouses all offer their own distinct advantages and disadvantages for data teams to consider.

Data Lake 52

Data Lake Data Warehouse Unstructured Data Raw Data 52

AltexSoft

MAY 14, 2021

And that’s the most important thing: Big Data analytics helps companies deal with business problems that couldn’t be solved with the help of traditional approaches and tools. This post will draw a full picture of what Big Data analytics is and how it works. Big Data and its main characteristics.

Big Data 78

Big Data Data Analytics IT NoSQL 78

Monte Carlo

JANUARY 12, 2024

We’ve previously discussed the need for quality over quantity when it comes to big data and, in this article, we’ll be looking at how recent technological innovations and new processes across 4 of the 5 ‘V’s of big data (volume, velocity, veracity, variety) are changing the future of big data analytics.

Big Data 59

Big Data Data Analytics Data Science Data Lake 59

Cloudera

JUNE 18, 2022

Cloudera customers run some of the biggest data lakes on earth. These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. On data warehouses and data lakes.

Data Lake 94

Data Lake Data Warehouse BI SQL 94

Cloudera

APRIL 22, 2021

Today’s enterprise data analytics teams are constantly looking to get the best out of their platforms. Storage plays one of the most important roles in the data platforms strategy, it provides the basis for all compute engines and applications to be built on top of it.

Pipeline-centric 101

Pipeline-centric Data Lake Hadoop Metadata 101

François Nguyen

MARCH 22, 2021

With this 3rd platform generation, you have more real time data analytics and a cost reduction because it is easier to manage this infrastructure in the cloud thanks to managed services. The data domain Discovery portal with all the metadata on the data life cycle 4.Federated

Technology 130

Technology Architecture Google Cloud Metadata 130

DataKitchen

NOVEMBER 4, 2021

Cloud computing has made it much easier to integrate data sets, but that’s only the beginning. Creating a data lake has become much easier, but that’s only ten percent of the job of delivering analytics to users. It often takes months to progress from a data lake to the final delivery of insights.

Process 98

Process Data Process Pharmaceutical Data Lake 98

Propel Data

OCTOBER 11, 2022

The main difference between data lakes and data warehouses is data lakes allow unstructured data, but data warehouses need structured data.

Data Lake 40

Data Lake Data Warehouse Unstructured Data Data Analytics 40

Snowflake

APRIL 18, 2024

How Snowflake Works An open-architecture deployment with a modern security data lake, and best-of-breed applications from Snowflake, can keep costs down while improving an organization’s security posture. A security data lake eliminates data silos by removing limits on ingest and retention.

Data Lake 109

Data Lake Data Ingestion Bytes Cloud Computing 109

Edureka

JUNE 1, 2023

This is where AWS Data Analytics comes into action, providing businesses with a robust, cloud-based data platform to manage, integrate, and analyze their data. In this blog, we’ll explore the world of Cloud Data Analytics and a real-life application of AWS Data Analytics.

AWS 52

AWS Data Analytics Cloud Amazon Web Services 52

KDnuggets

JANUARY 18, 2023

7 Best Platforms to Practice SQL • Explainable AI: 10 Python Libraries for Demystifying Your Model's Decisions • ChatGPT: Everything You Need to Know • Data Lakes and SQL: A Match Made in Data Heaven • Google Data Analytics Certification Review for 2023

SQL 86

SQL Python Data Lake Certification 86

Knowledge Hut

OCTOBER 6, 2023

Recently, the AWS Data Analytics Certification has captured my attention, and I have been researching the many AWS data analytics certification benefits. I'll delve into the specifics in this post to help you determine if AWS Data Analytics certification is worth it. What is AWS Data Analytics?

AWS 52

AWS Certification Data Analytics IT 52

Edureka

APRIL 9, 2025

Imagine being in charge of creating an intelligent data universe where collaboration, analytics, and artificial intelligence all work together harmoniously. Development of Some Relevant Skills and Knowledge Data Engineering Fundamentals: Theoretical knowledge of data loading patterns, data architectures, and orchestration processes.

Engineering 40

Engineering Data Ingestion Data Lake Programming Language 40

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?

Pharmaceutical 98

Pharmaceutical Data Lake Data Architecture Architecture 98

Cloudera

MAY 30, 2024

Cloudera customers run some of the biggest data lakes on earth. These lakes power mission-critical, large-scale data analytics and AI use cases—including enterprise data warehouses.

Data Lake 74

Data Lake Data Warehouse Programming Language Data Ingestion 74

DataKitchen

NOVEMBER 29, 2021

If data analytics is like a factory, the DataOps Engineer owns the assembly line used to build a data and analytic product. Most organizations run the data factory using manual labor. For example, a Hub-Spoke architecture could integrate data from a multitude of sources into a data lake.

Data Lake 98

Data Lake Manufacturing Architecture Data Architecture 98

Christophe Blefari

JANUARY 20, 2024

You'll be seen as the most technical person of a data team and you'll need to help regarding "low-level" stuff you team. You'll be also asked to put in place a data infrastructure. It means a data warehouse, a data lake or other concepts starting with data.

Data Engineer 130

Data Engineer Data Engineering Engineering Hadoop 130

Cloudera

NOVEMBER 18, 2020

It hosts over 150 big data analytics sandboxes across the region with over 200 users utilizing the sandbox for data discovery. With this functionality, business units can now leverage big data analytics to develop better and faster insights to help achieve better revenues, higher productivity, and decrease risk. .

Medical 123

Medical Banking Telecommunication Government 123

Cloudera

NOVEMBER 17, 2022

The Solution: CDP Private Cloud brings a next-generation hybrid architecture with cloud-native benefits to HBL’s data platform. HBL started their data journey in 2019 when data lake initiative was started to consolidate complex data sources and enable the bank to use single version of truth for decision making.

Banking 85

Banking Management Data Lake Professional Services 85

Knowledge Hut

DECEMBER 26, 2023

What is data analytics? In the world of IT, every small bit of data count; even information that looks like pure nonsense has its significance. So, how do we retrieve the significance from this data? This is where Data Science and analytics comes into the picture. Why data analytics?

Certification 52

Certification Data Analytics BI AWS 52

Ripple Engineering

JULY 9, 2024

We recently embarked on a significant data platform migration, transitioning from Hadoop to Databricks, a move motivated by our relentless pursuit of excellence and our contributions to the XRP Ledger's (XRPL) data analytics. Why Databricks Emerged as the Top Contender 1.

Hadoop 96

Hadoop Data Lake Machine Learning Raw Data 96

Monte Carlo

FEBRUARY 13, 2025

The Gartner Data & Analytics Summit offers an immersive learning experience tailored to help you: Stay Competitive : Hear real-life success stories and learn best practices that can be directly applied to your own data strategies.

Data Analytics 52

Data Analytics Government Data Architecture Data Lake 52

Data Engineering Podcast

MARCH 18, 2019

Summary Delivering a data analytics project on time and with accurate information is critical to the success of any business. In this episode Chris Bergh, head chef of Data Kitchen, explains how DataOps differs from DevOps, how the industry has begun adopting DataOps, and how to adopt an agile approach to building your data platform.

Machine Learning 100

Machine Learning Data Lake Manufacturing Big Data 100

Cloud Academy

MAY 2, 2018

Big Data Analytics on Azure Azure’s robust services make it easy and cost-effectivee to incorporate big data analysis into your cloud applications. This learning path focuses on getting your team up to speed using two key Azure services: Data Lake Analytics and Stream Analytics. What’s Next?

Google Cloud 52

Google Cloud Machine Learning Big Data AWS 52

Cloudera

JUNE 13, 2024

After countless open-source innovations ushered in the Big Data era, including the first commercial distribution of HDFS (Apache Hadoop Distributed File System), commonly referred to as Hadoop, the two companies joined forces, giving birth to an entire ecosystem of technology and tech companies. That’s today’s Cloudera.

Hadoop 103

Hadoop Big Data Banking Insurance 103

DataKitchen

AUGUST 19, 2021

Figure 3 shows an example processing architecture with data flowing in from internal and external sources. Each data source is updated on its own schedule, for example, daily, weekly or monthly. The data scientists and analysts have what they need to build analytics for the user. The new Recipes run, and BOOM! Conclusion.

Pharmaceutical 98

Pharmaceutical Data Lake Data Warehouse Raw Data 98

Striim

SEPTEMBER 11, 2024

This method is advantageous when dealing with structured data that requires pre-processing before storage. Conversely, in an ELT-based architecture, data is initially loaded into storage systems such as data lakes in its raw form. Would the data be stored on cloud or on-premises?’

Data Pipeline 98

Data Pipeline Designing Data Lake Data Warehouse 98

Cloudera

JANUARY 18, 2022

As a result of this innovative data solution, the company helped customers while keeping its default rate low. . The bank also used its data lake to feed a real-time dashboard that tracked employee health which led to better support for employees. As a result of the pandemic, everyone is doing more online.

Banking 96

Banking Recruitment Data Lake Data 96

Data Engineering Podcast

OCTOBER 5, 2020

Summary Analytical workloads require a well engineered and well maintained data integration process to ensure that your information is reliable and up to date. Building a real-time pipeline for your data lakes and data warehouses is a non-trivial effort, requiring a substantial investment of time and energy.

Data Integration 100

Data Integration Kafka Data Lake Machine Learning 100