Knowledge Hut

APRIL 25, 2024

Each of these technologies has its own strengths and weaknesses, but all of them can be used to gain insights from large data sets. As organizations continue to generate more and more data, big data technologies will become increasingly essential. Let's explore the technologies available for big data.

Big Data 98

Big Data Technology NoSQL Hadoop 98

Monte Carlo

MAY 28, 2024

Data Transformation : Clean, format, and convert extracted data to ensure consistency and usability for both batch and real-time processing. Data Loading : Load transformed data into the target system, such as a data warehouse or data lake. Used for identifying and cataloging data sources.

Data Ingestion 52

Data Ingestion Architecture Designing Hadoop 52

Christophe Blefari

AUGUST 4, 2023

The modern data stack as a collection of tools which interacts altogether to serve data to consumers is still relevant. Personally I think that the modern data stack characterises by having a central data storage in which everything happens. DuckDB is not really a data warehouse.

Google Cloud 225

Google Cloud MongoDB NoSQL Data 225

Christophe Blefari

SEPTEMBER 25, 2023

At the same time Microsoft leaked 38To of data — through a Github repository containing a link to an Azure storage with public access open. A guide to the Snowflake results cache — Cache is a critical piece to every data warehouse either for reusing data between runs or between stages in the same run.

Data 130

Data Data Warehouse Data Storage Data Pipeline 130

Christophe Blefari

SEPTEMBER 25, 2023

At the same time Microsoft leaked 38To of data — through a Github repository containing a link to an Azure storage with public access open. A guide to the Snowflake results cache — Cache is a critical piece to every data warehouse either for reusing data between runs or between stages in the same run.

Data 130

Data Data Warehouse Data Storage Data Pipeline 130

Data Engineering Weekly

DECEMBER 2, 2023

[link] Amazon S3 Express One Zone is a high-performance, single-availability Zone storage class purpose-built to deliver consistent single-digit millisecond data access for your most frequently accessed data and latency-sensitive applications. There are two critical properties of data warehouse access patterns.

IT 85

IT BI AWS Kafka 85

Christophe Blefari

NOVEMBER 11, 2022

I'll speak about "How to build the data dream team" Let's jump onto the news. Ingredients of a Data Warehouse Going back to basics. Kovid wrote an article that tries to explain what are the ingredients of a data warehouse. And he does it well. In the post Kovid details every idea.

BI 130

BI Data Warehouse Data Database 130

The Modern Data Company

MAY 10, 2023

In our previous post, The Pros and Cons of Leading Data Management and Storage Solutions , we untangled the differences among data lakes, data warehouses, data lakehouses, data hubs, and data operating systems. Does not have the resources to implement robust data governance and management.

Data Management 52

Data Management Data Lake Management Data Warehouse 52

The Modern Data Company

MAY 10, 2023

In our previous post, The Pros and Cons of Leading Data Management and Storage Solutions , we untangled the differences among data lakes, data warehouses, data lakehouses, data hubs, and data operating systems. Does not have the resources to implement robust data governance and management.

Data Management 52

Data Management Data Lake Management Data Warehouse 52

The Modern Data Company

MAY 10, 2023

In our previous post, The Pros and Cons of Leading Data Management and Storage Solutions , we untangled the differences among data lakes, data warehouses, data lakehouses, data hubs, and data operating systems. Does not have the resources to implement robust data governance and management.

Data Management 52

Data Management Data Lake Management Data Warehouse 52

Databand.ai

JULY 19, 2023

A Beginner’s Guide [SQ] Niv Sluzki July 19, 2023 ELT is a data processing method that involves extracting data from its source, loading it into a database or data warehouse, and then later transforming it into a format that suits business needs. The data is loaded as-is, without any transformation.

Data Cleanse 52

Data Cleanse Raw Data Data Storage Data Warehouse 52

Knowledge Hut

MARCH 28, 2024

Job Role 1: Azure Data Engineer Azure Data Engineers develop, deploy, and manage data solutions with Microsoft Azure data services. They use many data storage, computation, and analytics technologies to develop scalable and robust data pipelines.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Warehouse 52

phData: Data Engineering

SEPTEMBER 19, 2023

This blog will guide you through the best data modeling methodologies and processes for your data lake, helping you make informed decisions and optimize your data management practices. What is a Data Lake? What are Data Modeling Methodologies, and Why Are They Important for a Data Lake?

Data Lake 52

Data Lake Process Metadata Data Warehouse 52

Monte Carlo

MARCH 28, 2023

As part of this movement, Fivetran and dbt fundamentally altered the data pipeline from ETL to ELT. Hightouch interrupted SaaS eating the world in an attempt to shift the center of gravity to the data warehouse. Other common light transformations done within the ingestion phase are data formatting and deduplication.

Data Warehouse 126

Data Warehouse Raw Data Data Pipeline Software Engineer 126

AltexSoft

AUGUST 29, 2023

In 2010, a transformative concept took root in the realm of data storage and analytics — a data lake. The term was coined by James Dixon , Back-End Java, Data, and Business Intelligence Engineer, and it started a new era in how organizations could store, manage, and analyze their data.

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

Monte Carlo

JANUARY 5, 2024

You know what they always say: data lakehouse architecture is like an onion. …ok, Data lakehouse architecture combines the benefits of data warehouses and data lakes, bringing together the structure and performance of a data warehouse with the flexibility of a data lake. But they should!

Architecture 52

Architecture Data Lake Metadata Unstructured Data 52

Monte Carlo

JANUARY 5, 2024

You know what they always say: data lakehouse architecture is like an onion. …ok, Data lakehouse architecture combines the benefits of data warehouses and data lakes, bringing together the structure and performance of a data warehouse with the flexibility of a data lake. But they should!

Architecture 52

Architecture Data Lake Metadata Unstructured Data 52

Monte Carlo

APRIL 27, 2023

Empowered by the rise of the modern data stack , leading companies like Warner Music Group , Chime and Petsmart are now turning to the Composable CDP to unlock a modular customer data architecture that centers on the cloud data warehouse. Why not build one single store of customer data to activate from centrally?

Data Warehouse 72

Data Warehouse Data Collection Architecture Data Storage 72

Christophe Blefari

SEPTEMBER 28, 2023

Historically, data pipelines were designed with an ETL approach, storage was expensive and we had to transform the data before using it. With the cloud, we got the—false—impression that resources were infinite and cheap, so we switched to ETL by pushing everything into a central data storage.

Cloud Storage 147

Cloud Storage Big Data Hadoop SQL 147

Cloudera

DECEMBER 12, 2018

After having rebuilt their data warehouse, I decided to take a little bit more of a pointed role, and I joined Oracle as a database performance engineer. I spent eight years in the real-world performance group where I specialized in high visibility and high impact data warehousing competes and benchmarks.

Data Warehouse 42

Data Warehouse Relational Database Hadoop BI 42

Towards Data Science

DECEMBER 1, 2023

This tool automates ELT (Extract, Load, Transform) process, integrating your data from the source system of Google Calendar to our Snowflake data warehouse. Storage —  Snowflake Snowflake, a cloud-based data warehouse tailored for analytical needs, will serve as our data storage solution.

Data Engineering 70

Data Engineering Data Engineer Project Engineering 70

The Modern Data Company

MAY 8, 2023

Data lakes, data warehouses, data hubs, data lakehouses, and data operating systems are data management and storage solutions designed to meet different needs in data analytics, integration, and processing. However, data warehouses can experience limitations and scalability challenges.

Data Management 52

Data Management Data Lake Management Data Governance 52

The Modern Data Company

MAY 8, 2023

Data lakes, data warehouses, data hubs, data lakehouses, and data operating systems are data management and storage solutions designed to meet different needs in data analytics, integration, and processing. However, data warehouses can experience limitations and scalability challenges.

Data Management 52

Data Management Data Lake Management Data Governance 52

The Modern Data Company

MAY 8, 2023

Data lakes, data warehouses, data hubs, data lakehouses, and data operating systems are data management and storage solutions designed to meet different needs in data analytics, integration, and processing. However, data warehouses can experience limitations and scalability challenges.

Data Management 52

Data Management Data Lake Management Data Governance 52

phData: Data Engineering

MARCH 11, 2024

For years, marketing teams across industries have turned to implementing traditional Customer Data Platforms (CDPs) as separate systems purpose-built to unlock growth with first-party data. The ELT platform offers 200+ pre-built connections to centralize data to any data platform. dbt has become the standard for modeling.

Data Warehouse 52

Data Warehouse Data Data Storage Cloud 52

Towards Data Science

DECEMBER 15, 2023

Taking a hard look at data privacy puts our habits and choices in a different context, however. Data scientists’ instincts and desires often work in tension with the needs of data privacy and security. Anyone who’s fought to get access to a database or data warehouse in order to build a model can relate.

Machine Learning 91

Machine Learning Data Science Data Security Data Storage 91

Knowledge Hut

NOVEMBER 17, 2023

Database Knowledge Data warehousing ideas like the star and snowflake schema, as well as how to design and develop a data warehouse, should be well understood by you. This involves knowing how to manage data partitions, load data into a data warehouse, and speed up query execution.

Data Engineering 52

Data Engineering Data Engineer Engineering Scala 52

Towards Data Science

APRIL 3, 2023

As part of this movement, Fivetran and dbt fundamentally altered the data pipeline from ETL to ELT. Hightouch interrupted SaaS eating the world in an attempt to shift the center of gravity to the data warehouse. Other common light transformations done within the ingestion phase are data formatting and deduplication.

Data Engineering 98

Data Engineering Data Engineer Engineering Data Warehouse 98

Monte Carlo

MAY 14, 2024

Depending on the quantity of data flowing through an organization’s pipeline — or the format the data typically takes — the right modern table format can help to make workflows more efficient, increase access, extend functionality, and even offer new opportunities to activate your unstructured data.

Data Lake 52

Data Lake Metadata Hadoop Data Governance 52

Knowledge Hut

JANUARY 18, 2024

BI developers must use cloud-based platforms to design, prototype, and manage complex data. To pursue a career in BI development, one must have a strong understanding of data mining, data warehouse design, and SQL. Roles and Responsibilities Write data collection and processing procedures.

Data Science 98

Data Science Business Analyst ETL Method Data Architect 98

Knowledge Hut

NOVEMBER 28, 2023

Hence, learning and developing the required data engineer skills set will ensure a better future and can even land you better salaries in good companies anywhere in the world. After all, data engineer skills are required to collect data, transform it appropriately, and make it accessible to data scientists.

Data Engineering 52

Data Engineering Data Engineer Engineering Generalist 52

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

Data Engineering Podcast

AUGUST 14, 2021

Are you bored with writing scripts to move data into SaaS tools like Salesforce, Marketo, or Facebook Ads? Hightouch is the easiest way to sync data into the platforms that your business teams rely on. The data you’re looking for is already in your data warehouse and BI tools. No more scripts, just SQL.

Unstructured Data 100

Unstructured Data Machine Learning Data Lake SQL 100

AltexSoft

MARCH 14, 2023

As the volume and complexity of data continue to grow, organizations seek faster, more efficient, and cost-effective ways to manage and analyze data. In recent years, cloud-based data warehouses have revolutionized data processing with their advanced massively parallel processing (MPP) capabilities and SQL support.

IT 59

IT Data Warehouse Data Governance Data Lake 59

Knowledge Hut

NOVEMBER 19, 2023

As a result, data engineers working with big data today require a basic grasp of cloud computing platforms and tools. Businesses can employ internal, public, or hybrid clouds depending on their data storage needs, including AWS, Azure, GCP, and other well-known cloud computing platforms.

Data Engineering 52

Data Engineering Data Engineer Engineering PostgreSQL 52

Cloudera

AUGUST 31, 2021

Cloudera and Accenture demonstrate strength in their relationship with an accelerator called the Smart Data Transition Toolkit for migration of legacy data warehouses into Cloudera Data Platform. Accenture’s Smart Data Transition Toolkit . Are you looking for your data warehouse to support the hybrid multi-cloud?

Data Warehouse 82

Data Warehouse Database-centric Metadata Cloud 82

Knowledge Hut

JANUARY 18, 2024

Working in big data, Microsoft has launched projects like AI for Earth, which uses artificial intelligence to enhance environmental quality, and AI for Accessibility, which uses artificial intelligence to improve the accessibility of people with disability. IBM is one of the best companies to work for in Data Science.

Data Science 98

Data Science Amazon Web Services Finance Big Data 98