AltexSoft

AUGUST 22, 2022

Some would say that it’s not a big deal, however, these mixed environments have resulted in the complexities of managing disjointed data and business processes. With these challenges in enterprise data management, there has to be an approach to overcoming them, right? Support for different data types and use cases.

Architecture 52

Architecture Metadata Data Lake Machine Learning 52

Ascend.io

JULY 19, 2023

While the journey will differ from company to company — because of their unique business and data needs — there are fundamental principles that provide a blueprint for action. Consider this your primer to stop overthinking, start acting, and truly harness the power of data mesh. Establish clear data governance policies.

Data Governance 40

Data Governance Government Metadata Data 40

Ascend.io

JUNE 8, 2023

Data Ingestion Data in today’s businesses come from an array of sources, including various clouds, APIs, warehouses, and applications. This multitude of sources often causes a dispersed, complex, and poorly structured data landscape. Data stewards are thus the best contributors to the content of data catalogs.

Pipeline-centric 52

Pipeline-centric Database-centric Data Ingestion Data Pipeline 52

AltexSoft

JUNE 26, 2023

Data collection as the first step in the decision-making process, driven by machine learning. In machine learning projects, data collection precedes such stages as data cleaning and preprocessing, model training and testing, and making decisions based on a model’s output. Data engineering explained in 14 minutes.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

AltexSoft

MAY 12, 2023

By understanding these aspects comprehensively, you can harness the true potential of unstructured data and transform it into a strategic asset. 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.

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

Data Engineering Weekly

MARCH 24, 2023

Why should we care about Data Creation Process? All Successful Data-Driven organizations have one thing in common; They have a high-quality & efficient data creation process. Data creation is often the differentiator between the success & the failure of a data team.

Engineering 67

Engineering Data Transportation Database 67

ProjectPro

JANUARY 24, 2023

With over 20 pre-built connectors and 40 pre-built transformers, AWS Glue is an extract, transform, and load (ETL) service that is fully managed and allows users to easily process and import their data for analytics. You can leverage AWS Glue to discover, transform, and prepare your data for analytics.

AWS 52

AWS Data Lake ETL Tools Scala 52

AltexSoft

JULY 29, 2022

Apache Hadoop is an open-source Java-based framework that relies on parallel processing and distributed storage for analyzing massive datasets. Developed in 2006 by Doug Cutting and Mike Cafarella to run the web crawler Apache Nutch, it has become a standard for Big Data analytics. How HDFS master-slave structure works.

Hadoop 59

Hadoop Big Data Google Cloud NoSQL 59

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. called “ N etflix M edia D ata B ase” (NMDB) that is used to address them.

Media 54

Media Metadata Data MongoDB 54

Grouparoo

JANUARY 11, 2022

When it comes to storing large volumes of data, a simple database will be impractical due to the processing and throughput inefficiencies that emerge when managing and accessing big data. This article looks at the options available for storing and processing big data, which is too large for conventional databases to handle.

Data Lake 52

Data Lake Data Warehouse Unstructured Data Raw Data 52

Monte Carlo

JANUARY 25, 2023

Batch in the warehouse Data warehouses tend to operate in a batch environment rather than using stream processing like we do when moving data from production services. One of the bigger differences between these two types of systems comes in how we think about processing data. Consistency in your tech stack.

Data Warehouse 52

Data Warehouse Data High Quality Data Metadata 52

ProjectPro

AUGUST 11, 2021

“Data Lake vs Data Warehouse = Load First, Think Later vs Think First, Load Later” The terms data lake and data warehouse are frequently stumbled upon when it comes to storing large volumes of data. Data is generally not loaded into a data warehouse unless a use case has been defined for the data.

Data Lake 52

Data Lake Data Warehouse Cloud Hadoop 52

Towards Data Science

FEBRUARY 15, 2023

In this context, data management in an organization is a key point for the success of its projects involving data. One of the main aspects of correct data management is the definition of a data architecture. show() The history object is a Spark Data Frame. Legend says, that this didn’t go well.

Data Lake 77

Data Lake Data Warehouse Hadoop Data Architecture 77

Netflix Tech

DECEMBER 14, 2018

A fundamental requirement for any lasting data system is that it should scale along with the growth of the business applications it wishes to serve. NMDB is built to be a highly scalable, multi-tenant, media metadata system that can serve a high volume of write/read throughput as well as support near real-time queries.

Media 94

Media Database Metadata Data Schemas 94

AltexSoft

MARCH 2, 2023

Data governance is a broad term that refers to a critical set of organizational policies, processes, roles, standards, and metrics for ensuring the accuracy, consistency, security, and availability of data as well as its effective use. Learn more about data integrity in our dedicated article.

Data Governance 52

Data Governance Government Healthcare Programming 52

AltexSoft

MARCH 30, 2023

Shell, Adobe, Burberry, Columbia, Bayer — you definitely know the names. The answer is simple: They use the same technology to make the most of data. Along with thousands of other data-driven organizations from different industries, the above-mentioned leaders opted for Databrick to guide strategic business decisions.

Scala 64

Scala Data Lake BI Google Cloud 64

AltexSoft

NOVEMBER 1, 2023

Named entity recognition (NER) is a subfield within natural language processing (NLP) that focuses on identifying and classifying specific data points from textual content. Word embeddings translate words or phrases into numerical vectors of fixed size, making it easier for machine learning models to process. POS tagging.

Deep Learning 52

Deep Learning Machine Learning Datasets Algorithm 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

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 Data Lake 40

ProjectPro

APRIL 26, 2016

Pig vs Hive Criteria Pig Hive Type of Data Apache Pig is usually used for semi structured data. Used for Structured Data Schema Schema is optional. Language It is a procedural data flow language. Partitioning in Hive helps prune the data when executing the queries to speed up processing.

Hadoop 40

Hadoop Metadata SQL Database 40

phData: Data Engineering

JULY 18, 2023

As an AI and data analytics consulting company, phData is on a mission to become the world leader in delivering data services and products on a modern data platform. Throughout this journey, we’ve helped hundreds of clients achieve eye-opening results by moving to the Modern Data Stack.

Data Warehouse 52

Data Warehouse Pipeline-centric Government Data 52

ProjectPro

OCTOBER 28, 2015

Apache Hadoop is synonymous with big data for its cost-effectiveness and its attribute of scalability for processing petabytes of data. Data analysis using hadoop is just half the battle won. Getting data into the Hadoop cluster plays a critical role in any big data deployment.

ETL Tools 52

ETL Tools Hadoop Relational Database Unstructured Data 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.

Hadoop 40

Hadoop Big Data Metadata Java 40

ProjectPro

OCTOBER 20, 2021

It is important to understand how data flows in the real world and what kind of AI interview questions are being discussed across companies. The value of a company lies solely in the interview process. It is a function to find the best model with minimal knowledge or effort from the Data Scientist.

Machine Learning 52

Machine Learning Algorithm Government Data Science 52

ProjectPro

DECEMBER 10, 2021

Worker role (allows apps to run by themselves without using IIS and helps run background processes). These cloud deployment models employ private cloud service features such as processing confidential data and public cloud services such as hosting commercial applications. What do you understand about the Azure SLA? of the time.

BI 52

BI Cloud Computing SQL Database 52