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. So let’s get to the bottom of the big question: what kind of data storage layer will provide the strongest foundation for your data platform?

Data Lake 52

Data Lake Data Warehouse Unstructured Data Raw Data 52

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

ProjectPro

FEBRUARY 8, 2023

AWS Glue is a widely-used serverless data integration service that uses automated extract, transform, and load ( ETL ) methods to prepare data for analysis. It offers a simple and efficient solution for data processing in organizations. Then, Glue writes the job's metadata into the embedded AWS Glue Data Catalog.

AWS 98

AWS Scala Metadata Data Lake 98

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

AltexSoft

JUNE 7, 2021

Hadoop and Spark are the two most popular platforms for Big Data processing. They both enable you to deal with huge collections of data no matter its format — from Excel tables to user feedback on websites to images and video files. Obviously, Big Data processing involves hundreds of computing units.

Big Data Tools 98

Big Data Tools Hadoop Big Data Database-centric 98

Knowledge Hut

DECEMBER 21, 2023

Few benefits of Cloud computing are listed below: Scalability: With Cloud computing we get scalable applications which suits for large scale production systems for Businesses which store and process large sets of data. A data redundancy layer, a blockchain layer, and a verification and recovery layer make up the mechanism.

Cloud Computing 52

Cloud Computing Cloud Algorithm Healthcare 52

ProjectPro

JANUARY 31, 2023

This process involves data collection from multiple sources, such as social networking sites, corporate software, and log files. Data Storage: The next step after data ingestion is to store it in HDFS or a NoSQL database such as HBase. Data Processing: This is the final step in deploying a big data model.

Big Data 52

Big Data Hadoop AWS Relational Database 52

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

Snowflake

APRIL 5, 2023

Traditionally, the dimensional data modeling approach is used to build complex data warehouses, while Data Vaults are used in data warehouses to offer long-term historical data storage while modeling. Why is data modeling important for a data warehouse?

Data Warehouse 52

Data Warehouse Healthcare Unstructured Data Metadata 52

ProjectPro

NOVEMBER 15, 2021

With SQL, machine learning, real-time data streaming, graph processing, and other features, this leads to incredibly rapid big data processing. DataFrames are used by Spark SQL to accommodate structured and semi-structured data. Calcite has chosen to stay out of the data storage and processing business.

Big Data 52

Big Data Project Metadata Programming Language 52

AltexSoft

NOVEMBER 10, 2021

In a nutshell, the lakehouse system leverages low-cost storage to keep large volumes of data in its raw formats just like data lakes. At the same time, it brings structure to data and empowers data management features similar to those in data warehouses by implementing the metadata layer on top of the store.

Architecture 52

Architecture Data Lake Data Warehouse Metadata 52

Grouparoo

JANUARY 11, 2022

A data warehouse is a unified repository where data from diverse sources undergo aggregation and integration into a usable source of information. To achieve this, a data warehouse will require processes to gather and integrate data, manage data quality, create metadata, and support any regulatory compliance and governance procedures.

Data Lake 52

Data Lake Data Warehouse Unstructured Data Raw Data 52

Knowledge Hut

NOVEMBER 28, 2023

Data engineers design, manage, test, maintain, store, and work on the data infrastructure that allows easy access to structured and unstructured data. Data engineers need to work with large amounts of data and maintain the architectures used in various data science projects. Technical Data Engineer Skills 1.Python

Data Engineering 52

Data Engineering Data Engineer Engineering Generalist 52

Snowflake

JULY 10, 2023

“California Air Resources Board has been exploring processing atmospheric data delivered from four different remote locations via instruments that produce netCDF files. Previously, working with these large and complex files would require a unique set of tools, creating data silos.

Unstructured Data 40

Unstructured Data Python Process Scala 40

ProjectPro

FEBRUARY 25, 2022

Data Ingestion Data Processing Data Splitting Model Training Model Evaluation Model Deployment Monitoring Model Performance Machine Learning Pipeline Tools Machine Learning Pipeline Deployment on Different Platforms FAQs What tools exist for managing data science and machine learning pipelines?

Machine Learning 52

Machine Learning Building Amazon Web Services AWS 52

Netflix Tech

OCTOBER 19, 2020

Distributed Tracing: the missing context in troubleshooting services at scale Prior to Edgar, our engineers had to sift through a mountain of metadata and logs pulled from various Netflix microservices in order to understand a specific streaming failure experienced by any of our members.

Building 93

Building Transportation Metadata Java 93

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

JULY 29, 2022

No matter the actual size, each cluster accommodates three functional layers — Hadoop distributed file systems for data storage, Hadoop MapReduce for processing, and Hadoop Yarn for resource management. It relieves the MapReduce engine of scheduling tasks and decouples data processing from resource management.

Hadoop 59

Hadoop Big Data Google Cloud NoSQL 59

AltexSoft

MAY 12, 2023

Without a fixed schema, the data can vary in structure and organization. File systems, data lakes, and Big Data processing frameworks like Hadoop and Spark are often utilized for managing and analyzing unstructured data. You can’t just keep it in SQL databases, unlike structured data.

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

ProjectPro

JANUARY 31, 2022

Snowflake Data Marketplace gives users rapid access to various third-party data sources. Moreover, numerous sources offer unique third-party data that is instantly accessible when needed. Snowflake's machine learning partners transfer most of their automated feature engineering down into Snowflake's cloud data platform.

Architecture 52

Architecture IT Data Warehouse Amazon Web Services 52

Databand.ai

JUNE 28, 2023

You can monitor how much data is being ingested, how quickly it’s being processed, and whether there are any errors or delays. Data processing : As data moves through various stages of processing, observability tools can monitor the operation of each stage. See Databand in action Databand.ai

Data Pipeline 98

Data Pipeline Data Engineering Data Engineer Engineering 98

Silectis

JANUARY 3, 2021

BI (Business Intelligence) Strategies and systems used by enterprises to conduct data analysis and make pertinent business decisions. Big Data Large volumes of structured or unstructured data. Big Query Google’s cloud data warehouse. Flat File A type of database that stores data in a plain text format.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

Knowledge Hut

SEPTEMBER 29, 2023

Microsoft Data Engineer Certification is one such certification which is most sought after by professionals. By combining data from various structured and unstructured data systems into structures, Microsoft Azure Data Engineers will be able to create analytics solutions.

Certification 52

Certification Data Engineering Data Engineer Engineering 52

Monte Carlo

JANUARY 12, 2024

On the data lake side, Databricks has launched Unity Catalog to help bring more metadata, structure, and governance to data assets. Real-time data/insights Being able to access real-time data for analysis might sound like overkill to some, but that’s just no longer the case.

Big Data 59

Big Data Data Analytics Data Science Data Lake 59

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

Monte Carlo

JANUARY 25, 2023

In this article, we’ll take a closer look at the data storage level of the data stack to determine when to invest in storage and compute tooling, what “build versus buy” really means when it comes to storage and compute, and how our five considerations might impact your decision. Let’s jump in!

Data Warehouse 40

Data Warehouse Building Data Lake Data Storage 40

AltexSoft

SEPTEMBER 21, 2023

Besides Elasticsearch, which is the hub for indexing, searching, and complex data analytics, the stacks include the following tools Beats are lightweight data shippers that are part of the Elastic Stack. Beats facilitate data movement from source to destination, which can be either Elasticsearch or Logstash, depending on the use case.

Engineering 52

Engineering NoSQL Programming Language Java 52

Towards Data Science

FEBRUARY 15, 2023

Concepts, theory, and functionalities of this modern data storage framework Photo by Nick Fewings on Unsplash Introduction I think it’s now perfectly clear to everybody the value data can have. To use a hyped example, models like ChatGPT could only be built on a huge mountain of data, produced and collected over years.

Data Lake 78

Data Lake Data Warehouse Hadoop Data Architecture 78

Knowledge Hut

DECEMBER 21, 2023

Different databases have different patterns of data storage. For instance, MongoDB stores data in a semi-structured pattern, Cassandra stores data in the form of columns, and Redis stores data as key-value pairs. Avro creates binary data which can be both compressed as well as split.

Hadoop 52

Hadoop Big Data NoSQL Unstructured Data 52

Monte Carlo

AUGUST 19, 2023

We’ll cover: What is a data platform? Below, we share what the “basic” data platform looks like and list some hot tools in each space (you’re likely using several of them): The modern data platform is composed of five critical foundation layers. Data Storage and Processing The first layer?

Building 52

Building BI Data Lake Data Governance 52

AltexSoft

OCTOBER 30, 2021

But with the start of the 21st century, when data started to become big and create vast opportunities for business discoveries, statisticians were rightfully renamed into data scientists. Data scientists today are business-oriented analysts who know how to shape data into answers, often building complex machine learning models.

Data Engineering 98

Data Engineering Data Engineer Engineering Machine Learning 98

ProjectPro

AUGUST 11, 2021

The data warehouse layer consists of the relational database management system (RDBMS) that contains the cleaned data and the metadata, which is data about the data. The RDBMS can either be directly accessed from the data warehouse layer or stored in data marts designed for specific enterprise departments.

Data Lake 52

Data Lake Data Warehouse Cloud Hadoop 52

Monte Carlo

JUNE 14, 2023

In this post, we will help you quickly level up your overall knowledge of data pipeline architecture by reviewing: Table of Contents What is data pipeline architecture? Why is data pipeline architecture important? Despite Hadoop’s parallel and distributed processing, compute was a limited resource as well.

Data Pipeline 52

Data Pipeline Architecture Data Lake Data Warehouse 52

ProjectPro

NOVEMBER 22, 2021

StructType is a collection of StructField objects that determines column name, column data type, field nullability, and metadata. To define the columns, PySpark offers the pyspark.sql.types import StructField class, which has the column name (String), column type (DataType), nullable column (Boolean), and metadata (MetaData).

Hadoop 52

Hadoop Python Datasets Metadata 52

ProjectPro

JUNE 22, 2017

“A hadoop cluster is a collection of independent components connected through a dedicated network to work as a single centralized data processing resource. ” “A computational computer cluster that distributes data analysis workload across various cluster nodes that work collectively to process the data in parallel.”

Hadoop 52

Hadoop IT Data Analysis Big Data 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

Knowledge Hut

JULY 26, 2023

Cassandra specializes in handling high-volume, high-velocity, and high-reliability data, making it perfect for real-time data processing and fault tolerance applications. Apache Cassandra): Instead of the usual row-wise technique employed by relational databases, columnar databases store data in columns.

Database 52

Database NoSQL Telecommunication MongoDB 52