Confluent

AUGUST 29, 2019

Kafka already allows you to look at data as streams or tables; graphs are a third option, a more natural representation with a lot of grounding in theory for some use cases. So we can improve a portion of just about any event streaming application by adding graph abilities to it. Here we go! Step 1: Graph the network with Neo4j.

Kafka 55

Kafka Process Algorithm Cloud 55

Engineering at Meta

FEBRUARY 6, 2024

In the event of a cache miss (indicated by exec failing with ENOENT ), DotSlash uses the information from the DotSlash file to determine the URL it should use to fetch the artifact containing the executable as well as the size and digest information it should use to verify the contents. as originally intended.

Metadata 123

Metadata Coding Building Project 123

Cloudera

APRIL 1, 2024

We scored the highest in hybrid, intercloud, and multi-cloud capabilities because we are the only vendor in the market with a true hybrid data platform that can run on any cloud including private cloud to deliver a seamless, unified experience for all data, wherever it lies.

Cloud 105

Cloud Unstructured Data Metadata Government 105

AltexSoft

JUNE 7, 2021

HDFS master-slave structure. A HDFS Master Node, called a NameNode , keeps metadata with critical information about system files (like their names, locations, number of data blocks in the file, etc.) and keeps track of storage capacity, a volume of data being transferred, etc. Data management and monitoring options.

Big Data Tools 98

Big Data Tools Hadoop Big Data Database-centric 98

Netflix Tech

OCTOBER 31, 2018

The curious reader might have noticed that a majority of these characteristics relate to properties of the data managed by NMDB. Specifically, structured data that is modeled around the notion of a media timeline, with additional spatial properties. Hence, we designed it primarily around the notion of timed events.

Media 54

Media Metadata Data MongoDB 54

Data Engineering Weekly

MARCH 24, 2023

Data engineering starts to add value to the business by capturing events at each step of the business process. The events are then further enriched and analyzed to bring visibility to business operations. Architectural patterns for Data Creation There are three types of architecture patterns in data creation.

Engineering 68

Engineering Data Transportation Database 68

Snowflake

MARCH 30, 2023

Snowpipe micro-batch into Snowflake: Either triggered through a cloud service provider’s messaging service (such as AWS SQS , Azure Event notification , or Google Pub/Sub ) or making calls to Snowpipe ’s REST API endpoints. Schema drift on a wide table structure needs an ALTER TABLE statement, whereas the tall table structure does not.

Engineering 105

Engineering Raw Data Data Science Machine Learning 105

Zalando Engineering

JANUARY 30, 2023

New playbooks are reviewed by the on-call team, shared as part of on-call handover or operational reviews, and practiced in game days, or as part of preparation for big events. Managing structured data in markdown is not ideal, despite the ability to use front matter for metadata.

Management 56

Management Metadata Software Engineer Software Engineering 56

AltexSoft

AUGUST 22, 2022

The self-service functionally allows the entire organization to find relevant data faster and gain valuable insights. Support for different data types and use cases. A data fabric supports structured, unstructured, and semi-structured data whether it comes in real-time or generated in batches. Data catalog.

Architecture 52

Architecture Metadata Data Lake Machine Learning 52

Rockset

DECEMBER 17, 2021

For those unfamiliar, DynamoDB makes database scalability a breeze, but with some major caveats.

SQL 52

SQL NoSQL Database Design Metadata 52

Rockset

APRIL 26, 2023

Some RTA databases handle inserts with high performance, but incur large penalties when processing updates or duplicates (Apache Pinot, for example), which often results in a delay between events being produced and the information in those events being available for queries. It also efficiently handles massive streaming data volumes.

Architecture 52

Architecture Transportation Data Lake Insurance 52

ProjectPro

FEBRUARY 16, 2023

Data integration with ETL has evolved from structured data stores with high computing costs to natural state storage with read operation alterations thanks to the agility of the cloud. Data integration with ETL has changed in the last three decades. AWS Glue has a central metadata repository called the Glue catalog.

AWS 52

AWS Data Management ETL Tools Management 52

AltexSoft

MAY 12, 2023

What is unstructured data? Definition and examples Unstructured data , in its simplest form, refers to any data that does not have a pre-defined structure or organization. It can come in different forms, such as text documents, emails, images, videos, social media posts, sensor data, etc.

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

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

Hepta Analytics

FEBRUARY 14, 2022

Disadvantages of a data lake are: Can easily become a data swamp data has no versioning Same data with incompatible schemas is a problem without versioning Has no metadata associated It is difficult to join the data Data warehouse stores processed data, mostly structured data.

Data Ingestion 52

Data Ingestion Data Engineering Data Engineer Engineering 52

AltexSoft

SEPTEMBER 23, 2021

The result of experimentation supplies downstream applications with prepared data. A data hub serves as a gateway to dispense the required data. So the use of unstructured or semi-structured data is also available in a data hub, since a data lake can be a part of it.

Architecture 52

Architecture Data Lake Unstructured Data Data Warehouse 52

ProjectPro

AUGUST 11, 2021

This means that a data warehouse is a collection of technologies and components that are used to store data for some strategic use. Data is collected and stored in data warehouses from multiple sources to provide insights into business data. Data from data warehouses is queried using SQL.

Data Lake 52

Data Lake Data Warehouse Cloud Hadoop 52

Striim

JANUARY 4, 2023

Maybe, you first load data into a data warehouse and later go on to load data into a data lake. Cover schemas in data contracts. On a technical level, data contracts handle schemas of entities and events. Cover semantics in data contracts. temperature).

PostgreSQL 52

PostgreSQL Data Warehouse Data Data Lake 52

ProjectPro

OCTOBER 28, 2015

Hadoop Sqoop and Hadoop Flume are the two tools in Hadoop which is used to gather data from different sources and load them into HDFS. Sqoop in Hadoop is mostly used to extract structured data from databases like Teradata, Oracle, etc., Source defines where the data is coming from, for instance a message queue or a file.

ETL Tools 52

ETL Tools Hadoop Relational Database Unstructured Data 52

Wayne Yaddow

MARCH 14, 2025

Data freshness propagation: No automatic tracking of data propagation delays across multiplemodels. Workaround: Implement custom metadata tracking scripts or use dbt Clouds freshness monitoring. Workaround: Maintain a backup table of previous transformation results and manually roll back using SQL commands.

Unstructured Data 52

Unstructured Data SQL Data Pipeline Data Validation 52

AltexSoft

MARCH 14, 2023

Moreover, over 20 percent of surveyed companies were found to be utilizing 1,000 or more data sources to provide data to analytics systems. These sources commonly include databases, SaaS products, and event streams. Databases store key information that powers a company’s product, such as user data and product data.

IT 59

IT Data Warehouse Data Governance Data Lake 59

AltexSoft

JULY 18, 2023

Spark SQL brings native support for SQL to Spark and streamlines the process of querying semistructured and structured data. When transformations are applied to RDDs, Spark records the metadata to build up a DAG, which reflects the sequence of computations performed during the execution of the Spark job.

Big Data 52

Big Data Data Process Process Hadoop 52

ProjectPro

NOVEMBER 22, 2021

StructType is a collection of StructField objects that determines column name, column data type, field nullability, and metadata. PySpark imports the StructType class from pyspark.sql.types to describe the DataFrame's structure. The uName and the event timestamp are then combined to make a tuple. appName('ProjectPro').getOrCreate()

Hadoop 52

Hadoop Python Datasets Metadata 52

Rockset

JANUARY 28, 2020

Aside from video data from each camera-equipped store, Standard deals with other data sets such as transactional data, store inventory data that arrive in different formats from different retailers, and metadata derived from the extensive video captured by their cameras.

Retail 40

Retail Google Cloud Raw Data SQL 40

ProjectPro

NOVEMBER 15, 2021

It serves as a distributed processing engine for both categories of data streams: unbounded and bounded. Support for stream and batch processing, comprehensive state management, event-time processing semantics, and consistency guarantee for the state are just a few of Flink's capabilities.

Big Data 52

Big Data Project Metadata Programming Language 52

Monte Carlo

NOVEMBER 20, 2023

The data is unique and free from duplicates. And the transformed data is free from anomalies. Data quality can be impacted by all sorts of events and errors within a pipeline or ingestion source—from distribution anomalies caused by a keying error to the natural entropy that exists within a complex data system.

Data 69

Data Government Data Governance Datasets 69

AltexSoft

JUNE 26, 2023

From the perspective of data science, all miscellaneous forms of data fall into three large groups: structured, semi-structured, and unstructured. Key differences between structured, semi-structured, and unstructured data. Note, though, that not any type of web scraping is legal.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

Rockset

AUGUST 2, 2023

The Windward Maritime AI platform Lastly, Windward wanted to move their entire platform from batch-based data infrastructure to streaming. This transition can support new use cases that require a faster way to analyze events that was not needed until now. They used MongoDB as their metadata store to capture vessel and company data.

Database-centric 52

Database-centric PostgreSQL Transportation Insurance 52

ProjectPro

AUGUST 21, 2015

Hadoop vs RDBMS Criteria Hadoop RDBMS Datatypes Processes semi-structured and unstructured data. Processes structured data. Schema Schema on Read Schema on Write Best Fit for Applications Data discovery and Massive Storage/Processing of Unstructured data. are all examples of unstructured data.

Hadoop 40

Hadoop Big Data Metadata Java 40

Monte Carlo

JUNE 28, 2023

The music seems like a missed opportunity to remind us of the 90s theme for the celebration event taking place later tonight with Salt-N-Peppa at the Chase Center, but I’m not an event planner for a reason. when you write in a Delta table you will now create the underlying metadata in all three formats: Delta, Hudi, and Iceberg.

Data Warehouse 52

Data Warehouse Scala Unstructured Data Government 52

ProjectPro

JANUARY 31, 2022

They just need to deliver their data and hand it over to Snowflake to manage. Easily Available- Snowflake Architecture is designed to be fully distributed, covering multiple zones and regions, and is highly fault-tolerant in the event of hardware failure. This layer stores the metadata needed to optimize a query or filter data.

Architecture 52

Architecture IT Data Warehouse Amazon Web Services 52

Monte Carlo

JANUARY 25, 2023

The contracts themselves should be created using well-established protocols for serializing and deserializing structured data such as Google’s Protocol Buffers (protobuf), Apache Avro, or even JSON. We can specify the fields of the contract in addition to metadata like ownership, SLA, and where the table is located.

Data Warehouse 52

Data Warehouse Data High Quality Data Metadata 52

AltexSoft

JULY 19, 2022

So, to avoid any confusion, please be aware that data mesh is NOT. a data fabric, which is a single environment consisting of a unified architecture, and services or technologies running on that architecture. ” Data as a product principle.

Architecture 52

Architecture Data Lake Medical Datasets 52

AltexSoft

NOVEMBER 1, 2023

The categories encompass a diverse range of subjects present within the text, including individuals’ names, geographic locations, organizational names, dates, events, and even specific quantitative values such as money and percentages. Key concepts of NER Named entities are not the only concept to understand within the NER world.

Deep Learning 52

Deep Learning Machine Learning Datasets Algorithm 52

AltexSoft

OCTOBER 8, 2021

Considered to be a leader in the field of data integration, Oracle Data Integrator (ODI) is a multi-functional solution that is part of Oracle’s data management ecosystem. The platform provides features for event-based , data-based, and service-based integration styles. Data profiling and cleansing.

Data Integration 52

Data Integration Hadoop Data Warehouse Data Lake 52

ProjectPro

AUGUST 24, 2021

Data Engineering Project for Beginners If you are a newbie in data engineering and are interested in exploring real-world data engineering projects, check out the list of data engineering project examples below. This big data project discusses IoT architecture with a sample use case.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

Monte Carlo

JULY 10, 2023

Missing values Incomplete data can sometimes look like missing values throughout a data set, such as: Missing salary numbers in HR data sets Missing phone numbers in a CRM Missing location data in a marketing campaign Missing blood pressure data in an EMR Missing transaction in a credit ledger And the list goes on.

Data Collection 40

Data Collection Data Governance Government Data 40