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

Monte Carlo

MARCH 28, 2023

And so it almost seems unfair that new ideas are already springing up to disrupt the disruptors: Zero-ETL has data ingestion in its sights AI and Large Language Models could transform transformation Data product containers are eyeing the table’s thrown as the core building block of data Are we going to have to rebuild everything (again)?

Data Warehouse 126

Data Warehouse Raw Data Data Pipeline Software Engineer 126

Monte Carlo

AUGUST 19, 2023

By integrating tools from a variety of vendors, a data platform enables a data engineering team to not only manage an organization’s data but also activate it for a domain’s use cases. In today’s data-driven landscape, building a data platform is no longer a nice-to-have, but a necessity for most organizations.

Building 52

Building BI Data Lake Data Governance 52

Towards Data Science

APRIL 3, 2023

And so it almost seems unfair that new ideas are already springing up to disrupt the disruptors: Zero-ETL has data ingestion in its sights AI and Large Language Models could transform transformation Data product containers are eyeing the table’s thrown as the core building block of data Are we going to have to rebuild everything (again)?

Data Engineering 98

Data Engineering Data Engineer Engineering Data Warehouse 98

Databand.ai

JUNE 28, 2023

Yet reality is of course more closely governed by Murphy’s law, and on the output side of the black box, you will often see a host of strange values and cryptic missing columns. Data engineers are scratching their heads and realizing that to correct, you must first observe. And why the discrepancy? See Databand in action Databand.ai

Data Pipeline 98

Data Pipeline Data Engineering Data Engineer Engineering 98

Cloudera

AUGUST 31, 2021

While this “data tsunami” may pose a new set of challenges, it also opens up opportunities for a wide variety of high value business intelligence (BI) and other analytics use cases that most companies are eager to deploy. . Traditional data warehouse vendors may have maturity in data storage, modeling, and high-performance analysis.

Data Warehouse 82

Data Warehouse Database-centric Metadata Cloud 82

AltexSoft

MARCH 14, 2023

Batch jobs are often scheduled to load data into the warehouse, while real-time data processing can be achieved using solutions like Apache Kafka and Snowpipe by Snowflake to stream data directly into the cloud warehouse. But this distinction has been blurred with the era of cloud data warehouses.

IT 59

IT Data Warehouse Data Governance Data Lake 59

Monte Carlo

JUNE 14, 2023

Why is data pipeline architecture important? This is frequently referred to as a 5 or 7 layer (depending on who you ask) data stack like in the image below. Here are some of the most common solutions that are involved in modern data pipelines and the role they play. Continuously review and optimize costs.

Data Pipeline 52

Data Pipeline Architecture Data Lake Data Warehouse 52

Snowflake

MAY 22, 2023

Cross-Cloud Snowgrid Account Replication expands replication beyond databases – general availability Account Replication, now generally available, expands replication beyond databases to account metadata and integrations, making business continuity truly turnkey. Visit our documentation page to learn more.

Healthcare 52

Healthcare Scala Medical Transportation 52

AltexSoft

MAY 12, 2023

Tools and platforms for unstructured data management Unstructured data collection Unstructured data collection presents unique challenges due to the information’s sheer volume, variety, and complexity. The process requires extracting data from diverse sources, typically via APIs. Data durability and availability.

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

AltexSoft

JUNE 26, 2023

Read our article on Hotel Data Management to have a full picture of what information can be collected to boost revenue and customer satisfaction in hospitality. While all three are about data acquisition, they have distinct differences. Find sources of relevant data. Choose data collection methods and tools.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

AltexSoft

JULY 29, 2022

According to the latest report by Allied Market Research , the Big Data platform will see the biggest rise in adoption in telecommunication, healthcare, and government sectors. Hadoop distributed file system or HDFS is a data storage technology designed to handle gigabytes to terabytes or even petabytes of data.

Hadoop 59

Hadoop Big Data Google Cloud NoSQL 59

AltexSoft

SEPTEMBER 21, 2023

Data in Elasticsearch is organized into documents, which are then categorized into indices for better search efficiency. Each document is a collection of fields, the basic data units to be searched. Fields in these documents are defined and governed by mappings akin to a schema in a relational database.

Engineering 52

Engineering NoSQL Programming Language Java 52

ProjectPro

NOVEMBER 15, 2021

It was built from the ground up for interactive analytics and can scale to the size of Facebook while approaching the speed of commercial data warehouses. Presto allows you to query data stored in Hive, Cassandra, relational databases, and even bespoke data storage. To contribute to this project, hop onto: [link] 19.DataHub

Big Data 52

Big Data Project Metadata Programming Language 52

Knowledge Hut

SEPTEMBER 29, 2023

The latest Azure exam from Microsoft is structured as follows: Design and implement data storage: Creating and implementing a storage structure, a partition, and a serving layer are tested in this portion (40–45%). You can browse the data lake files with the interactive training material.

Certification 52

Certification Data Engineering Data Engineer Engineering 52

Snowflake

MARCH 30, 2023

3EJHjvm Once a business need is defined and a minimal viable product ( MVP ) is scoped, the data management phase begins with: Data ingestion: Data is acquired, cleansed, and curated before it is transformed. Feature engineering: Data is transformed to support ML model training. ML workflow, ubr.to/3EJHjvm

Engineering 83

Engineering Raw Data Data Science Scala 83

phData: Data Engineering

AUGUST 4, 2023

Data storage is a vital aspect of any Snowflake Data Cloud database. Within Snowflake, data can either be stored locally or accessed from other cloud storage systems. Snowflake hides user data objects and makes them accessible only through SQL queries through the compute layer.

Cloud Storage 52

Cloud Storage Google Cloud Amazon Web Services Data Storage 52

Cloudera

JANUARY 22, 2019

Forrester describes Big Data Fabric as, “A unified, trusted, and comprehensive view of business data produced by orchestrating data sources automatically, intelligently, and securely, then preparing and processing them in big data platforms such as Hadoop and Apache Spark, data lakes, in-memory, and NoSQL.”.

Big Data 44

Big Data NoSQL Data Lake Hadoop 44

phData: Data Engineering

JULY 18, 2023

Why Migrate to a Modern Data Stack? Zero Copy Cloning: Create multiple ‘copies’ of tables, schemas, or databases without actually copying the data. This noticeably saves time on copying and drastically reduces data storage costs. However, merely knowing what it consists of isn’t enough.

Data Warehouse 52

Data Warehouse Pipeline-centric Government Data 52