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

OCTOBER 6, 2021

This provided a nice overview of the breadth of topics that are relevant to data engineering including data warehouses/lakes, pipelines, metadata, security, compliance, quality, and working with other teams. For example, grouping the ones about metadata, discoverability, and column naming might have made a lot of sense.

Data Engineering 52

Data Engineering Data Engineer Engineering Pipeline-centric 52

Knowledge Hut

DECEMBER 21, 2023

NoSQL This database management system has been designed in a way that it can store and handle huge amounts of semi-structured or unstructured data. Avro creates binary data which can be both compressed as well as split. Avro creates a file that stores all the data and saves the schema in the metadata section.

Hadoop 52

Hadoop Big Data NoSQL Unstructured Data 52

AltexSoft

AUGUST 29, 2023

Instead of relying on traditional hierarchical structures and predefined schemas, as in the case of data warehouses, a data lake utilizes a flat architecture. This structure is made efficient by data engineering practices that include object storage. Watch our video explaining how data engineering works.

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

AltexSoft

FEBRUARY 11, 2023

Hands-on experience with a wide range of data-related technologies The daily tasks and duties of a data architect include close coordination with data engineers and data scientists. The candidates for this certification should be able to transform, integrate and consolidate both structured and unstructured data.

Data Architect 87

Data Architect Certification Generalist Big Data 87

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. Cassandra A database built by the Apache Foundation.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

Towards Data Science

MARCH 5, 2024

This comes with the advantages of reduction of redundancy, data integrity and consequently, less storage usage. Photo by Shubham Dhage on Unsplash While data normalization holds merit in traditional relational databases, the paradigm shifts when dealing with modern analytics platforms like BigQuery.

Bytes 70

Bytes Google Cloud Cloud Storage Utilities 70

Cloudera

AUGUST 31, 2021

Running on CDW is fully integrated with streaming, data engineering, and machine learning analytics. It has a consistent framework that secures and provides governance for all data and metadata on private clouds, multiple public clouds, or hybrid clouds. Consideration of both data & metadata in the migration.

Data Warehouse 82

Data Warehouse Database-centric Metadata Cloud 82

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. It comes with programming interfaces for entire clusters.

Big Data 52

Big Data Project Metadata Programming Language 52

Cloudera

JUNE 16, 2022

Use cases like fraud detection, network threat analysis, manufacturing intelligence, commerce optimization, real-time offers, instantaneous loan approvals, and more are now possible by moving the data processing components up the stream to address these real-time needs. . Without context, streaming data is useless.”

Kafka 86

Kafka Manufacturing Data Lake SQL 86

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

Knowledge Hut

JANUARY 3, 2024

In S3, data consists of the following components – key (name), value (data), version ID, metadata and access control lists. Data objects are stored redundantly across multiple devices in several locations. They are made for use as transactional databases and are suitable for storing structured and relational data.

AWS 52

AWS Amazon Web Services Certification Relational Database 52

AltexSoft

JULY 29, 2022

A master node called NameNode maintains metadata with critical information, controls user access to the data blocks, makes decisions on replications, and manages slaves. It relieves the MapReduce engine of scheduling tasks and decouples data processing from resource management. Low speed and no real-time data processing.

Hadoop 59

Hadoop Big Data Google Cloud NoSQL 59

phData: Data Engineering

AUGUST 4, 2023

Snowflake’s ‘staging area’ is a specific storage location where raw files are first loaded before they’re imported into the Snowflake database. 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

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

AltexSoft

DECEMBER 23, 2022

ELT makes it easier to manage and access all this information by allowing both raw and cleaned data to be loaded and stored for further analysis. With the ETL shift from a traditional on-premise variant to a cloud solution, you can also use it to work with different data sources and move a lot of data. Full extraction.

Process 52

Process Building Raw Data Data Lake 52

AltexSoft

MAY 12, 2023

Structured data is formatted in tables, rows, and columns, following a well-defined, fixed schema with specific data types, relationships, and rules. A fixed schema means the structure and organization of the data are predetermined and consistent. Without a fixed schema, the data can vary in structure and organization.

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

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

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

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. In a data warehouse, the data is generally processed.

Data Lake 52

Data Lake Data Warehouse Cloud Hadoop 52

AltexSoft

OCTOBER 8, 2021

The prevailing part of users claim that it is quite easy to configure and manage data flows with Oracle’s graphical tools. Data profiling and cleansing. The tool supports all sorts of data loading and processing: real-time, batch, streaming (using Spark), etc. Data loading. Pre-built connectors. Pricing model.

Data Integration 52

Data Integration Hadoop Data Warehouse Data Lake 52

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

ProjectPro

OCTOBER 28, 2015

The major difference between Sqoop and Flume is that Sqoop is used for loading data from relational databases into HDFS while Flume is used to capture a stream of moving data. Table of Contents Hadoop ETL tools: Sqoop vs Flume-Comparison of the two Best Data Ingestion Tools What is Sqoop in Hadoop?

ETL Tools 52

ETL Tools Hadoop Relational Database Unstructured Data 52

U-Next

SEPTEMBER 29, 2022

A structured data record consists of a very fixed field of data. Relational databases, spreadsheets, and other documents can contain this type of data. There is also the possibility of semi-structured data being a cross between these two types of data.

Management 52

Management Unstructured Data Data Government 52

ProjectPro

OCTOBER 15, 2014

Hive- Performance Benchmarking Hive vs Pig Pig vs Hive - Differences Pig Hive Procedural Data Flow Language Declarative SQLish Language For Programming For creating reports Mainly used by Researchers and Programmers Mainly used by Data Analysts Operates on the client side of a cluster. Does not have a dedicated metadata database.

Hadoop 52

Hadoop Unstructured Data Java SQL 52