phData: Data Engineering

SEPTEMBER 19, 2023

With the amount of data companies are using growing to unprecedented levels, organizations are grappling with the challenge of efficiently managing and deriving insights from these vast volumes of structured and unstructured data. Want to learn more about data governance?

Data Lake 52

Data Lake Process Metadata Data Warehouse 52

ProjectPro

FEBRUARY 16, 2023

While both BI and AI provide data-driven insights, they differ in how they help businesses gain a competitive edge in the data-driven marketplace. The blog will also guide you through how combining AI and BI will help improve business solutions. Focus Historical data analysis, reporting, and visualization.

Business Intelligence 52

Business Intelligence BI Data Mining Raw Data 52

Monte Carlo

AUGUST 31, 2023

Your downstream data consumers including product analysts, marketing leaders, and sales teams rely on data-driven tools like CRMs, CXPs, CMSs, and any other acronym under the sun to do their jobs quickly and effectively. But what happens when the data is wrong?

Data Lake 52

Data Lake Data Pipeline Unstructured Data Data Warehouse 52

Knowledge Hut

JULY 26, 2023

Veracity meaning in big data is the degree of accuracy and trustworthiness of data, which plays a pivotal role in deriving meaningful insights and making informed decisions. This blog will delve into the importance of veracity in Big Data, exploring why accuracy matters and how it impacts decision-making processes.

Big Data 52

Big Data Data Cleanse Retail Healthcare 52

ProjectPro

DECEMBER 7, 2021

Data pipelines are a significant part of the big data domain, and every professional working or willing to work in this field must have extensive knowledge of them. In broader terms, two types of data -- structured and unstructured data -- flow through a data pipeline. What is a Big Data Pipeline?

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 52

ProjectPro

NOVEMBER 17, 2021

In this blog, you’ll learn more about the benefits of sentiment analysis and ten project ideas divided by difficulty level. Access the Sentiment Analysis Project on Product Reviews with Source Code Get FREE Access to Machine Learning Example Codes for Data Cleaning, Data Munging, and Data Visualization 2.

Coding 52

Coding Project Entertainment Datasets 52

ProjectPro

SEPTEMBER 14, 2016

Many ProjectPro students looking to make transition into big data hadoop careers often want to know in detail about the hadoop developer job roles and responsibilities before they enrol for a hadoop training. Here’s a blog post that answers the question and details out the job responsibilities of a hadoop developer.

Hadoop 40

Hadoop Unstructured Data Java Big Data 40

ProjectPro

SEPTEMBER 26, 2014

The toughest challenges in business intelligence today can be addressed by Hadoop through multi-structured data and advanced big data analytics. Big data technologies like Hadoop have become a complement to various conventional BI products and services. Big data, multi-structured data, and advanced analytics.

Business Intelligence 40

Business Intelligence Hadoop BI Relational Database 40

ProjectPro

OCTOBER 18, 2021

From the outset of machine learning, it was challenging to work with unstructured data (image dataset) and transform it into structured data (texts). Access Data Science and Machine Learning Project Code Examples 15. Stanford Question Answering Dataset (SQuAD) is another comprehension-based dataset.

Machine Learning 52

Machine Learning Project Datasets Algorithm 52

Cloudera

MAY 14, 2024

This form of hybrid also goes a level deeper than one may find in a standard hybrid cloud, accounting for the entirety of the data lifecycle, whether that’s the point of ingestion, warehousing, or machine learning—even when that end-to-end data lifecycle is split between entirely different environments. Data comes in many forms.

Cloud 85

Cloud Data Governance Unstructured Data Data Architecture 85

ProjectPro

MAY 20, 2015

There are several big data and business analytics companies that offer a novel kind of big data innovation through unprecedented personalization and efficiency at scale. Which big data analytic companies are believed to have the biggest potential?

Big Data 40

Big Data Hadoop Business Analyst Unstructured Data 40

ProjectPro

SEPTEMBER 11, 2015

Learning Hadoop will ensure that you can build a secure career in Big Data. Big Data is not going to go away. There will always be a place for RDBMS, ETL, EDW and BI for structured data. But at the pace and nature at which big data is growing, technologies like Hadoop will be very necessary to tackle this data.

Hadoop 52

Hadoop Java BI Big Data 52

Snowflake

NOVEMBER 2, 2023

Rather than defining schema upfront, a user can decide which data and schema they need for their use case. Snowflake has long supported semi-structured data types and file formats like JSON, XML, Parquet, and more recently storage and processing of unstructured data such as PDF documents, images, videos, and audio files.

Data Lake 89

Data Lake Data Warehouse Cloud Unstructured Data 89

Monte Carlo

JANUARY 16, 2024

As every company becomes a data company, and more users within these companies are discovering new uses for previously unavailable data, existing infrastructure and tools are not just meeting that demand but creating new demands. At the center of it all is the data warehouse, the lynchpin of any modern data stack.

Data Lake 52

Data Lake Data Warehouse Unstructured Data AWS 52

U-Next

SEPTEMBER 7, 2022

Structuring data refers to converting unstructured data into tables and defining data types and relationships based on a schema. The data lakes store data from a wide variety of sources, including IoT devices, real-time social media streams, user data, and web application transactions.

Data Lake 52

Data Lake Data Warehouse Unstructured Data Amazon Web Services 52

Cloudera

NOVEMBER 25, 2020

The challenges Matthew and his team are facing are mainly about access to a multitude of data sets, of various types and sources, with ease and ad-hoc, and their ability to deliver data-driven and confident outcomes. . Most of their research data is unstructured and has a lot of variety. Challenges Ahead.

Data Warehouse 57

Data Warehouse Unstructured Data Medical Pharmaceutical 57

Knowledge Hut

JULY 24, 2023

In this blog, we will talk about the future of database management. NoSQL Databases NoSQL databases are non-relational databases (that do not store data in rows or columns) more effective than conventional relational databases (databases that store information in a tabular format) in handling unstructured and semi-structured data.

Database 52

Database NoSQL Management Relational Database 52

Cloudera

JULY 26, 2021

In fact, data product development introduces an additional requirement that wasn’t as relevant in the past as it is today: That of scalability in permissioning and authorization given the number and multitude of different roles of data constituents, both internal and external accessing a data product.

Generalist 115

Generalist Telecommunication Healthcare Data 115

Cloudera

SEPTEMBER 12, 2022

First, organizations have a tough time getting their arms around their data. More data is generated in ever wider varieties and in ever more locations. Organizations don’t know what they have anymore and so can’t fully capitalize on it — the majority of data generated goes unused in decision making. Open data lakehouse.

Unstructured Data 72

Unstructured Data Data Lake Data Architecture Data 72

Knowledge Hut

NOVEMBER 17, 2023

Today, data is everything, and every technology runs around managing, storing, accessing, and processing this data. After the introduction of cloud computing, the need for managing expanding data is getting more critical. Below are the benefits of why data scientists across the globe highly adopt AWS.

AWS 52

AWS Data Science Certification Amazon Web Services 52

ProjectPro

JANUARY 27, 2023

If you're wondering how the ETL process can drive your company to a new era of success, this blog will help you discover what use cases of ETL make it a critical component in many data management and analytic systems. ETL for IoT - Use ETL to analyze large volumes of data IoT devices generate.

BI 52

BI ETL Tools Retail Healthcare 52

Snowflake

MARCH 30, 2023

Data Vault as a practice does not stipulate how you transform your data, only that you follow the same standards to populate business vault link and satellite tables as you would to populate raw vault link and satellite tables. Based on Tecton blog So is this similar to data engineering pipelines into a data lake/warehouse?

Engineering 82

Engineering Raw Data Data Science Scala 82

Knowledge Hut

DECEMBER 26, 2023

The spectrum of sources from which data is collected for the study in Data Science is broad. These data have been accessible to us because of the advanced and latest technologies which are used in the collection of data. As a Data Engineer, you are expected to ask many questions.

Data Engineering 98

Data Engineering Data Engineer Engineering Pipeline-centric 98

Monte Carlo

APRIL 1, 2021

But while the technologies powering our access and analysis of data have matured, the mechanics behind understanding this data in a distributed environment have lagged behind. Here’s where data catalogs fall short and how data discovery platforms and tools can help ensure your data lake doesn’t turn into a data swamp.

Data Lake 52

Data Lake Unstructured Data Data Warehouse Metadata 52

Edureka

AUGUST 2, 2023

Raw data, however, is frequently disorganised, unstructured, and challenging to work with directly. Data processing analysts can be useful in this situation. Let’s take a deep dive into the subject and look at what we’re about to study in this blog: Table of Contents What Is Data Processing Analysis?

Data Process 52

Data Process Process Data Cleanse Data Mining 52

Cloudera

SEPTEMBER 15, 2022

Today’s platform owners, business owners, data developers, analysts, and engineers create new apps on the Cloudera Data Platform and they must decide where and how to store that data. Structured data (such as name, date, ID, and so on) will be stored in regular SQL databases like Hive or Impala databases.

Systems 86

Systems Hadoop Metadata Telecommunication 86

Edureka

FEBRUARY 9, 2023

This position requires knowledge of Microsoft Azure services such as Azure Data Factory, Azure Stream Analytics, Azure Databricks, Azure Cosmos DB, and Azure Storage. Azure Data Engineers Jobs – The Demand Azure Data Engineer Skills What does an Azure Data Engineer Do? Who is an Azure Data Engineer?

Data Engineering 52

Data Engineering Data Engineer Engineering Data Mining 52

ProjectPro

JANUARY 19, 2022

Planning to land a successful job as an Azure Data Engineer? Read this blog till the end to learn more about the roles and responsibilities, necessary skillsets, average salaries, and various important certifications that will help you build a successful career as an Azure Data Engineer.

Data Engineering 52

Data Engineering Data Engineer Engineering Scala 52

ProjectPro

JANUARY 31, 2023

If you're looking to break into the exciting field of big data or advance your big data career, being well-prepared for big data interview questions is essential. Get ready to expand your knowledge and take your big data career to the next level! But the concern is - how do you become a big data professional?

Big Data 52

Big Data Hadoop AWS Relational Database 52

ProjectPro

JULY 27, 2021

This blog is your one-stop solution for the top 100+ Data Engineer Interview Questions and Answers. In this blog, we have collated the frequently asked data engineer interview questions based on tools and technologies that are highly useful for a data engineer in the Big Data industry.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

Cloudera

SEPTEMBER 6, 2018

It supports a variety of storage engines that can handle raw files, structured data (tables), and unstructured data. It also supports a number of frameworks that can process data in parallel, in batch or in streams, in a variety of languages. Cloudera Enterprise.

Banking 40

Banking Machine Learning Big Data Scala 40

ProjectPro

JANUARY 24, 2023

Tired of relentlessly searching for the most effective and powerful data warehousing solutions on the internet? This blog is your comprehensive guide to Google BigQuery, its architecture, and a beginner-friendly tutorial on how to use Google BigQuery for your data warehousing activities. Search no more! Did you know ?

Bytes 52

Bytes Google Cloud Data Warehouse Datasets 52

AltexSoft

MAY 14, 2021

A single car connected to the Internet with a telematics device plugged in generates and transmits 25 gigabytes of data hourly at a near-constant velocity. And most of this data has to be handled in real-time or near real-time. Variety is the vector showing the diversity of Big Data. Data storage and processing.

Big Data 78

Big Data Data Analytics IT NoSQL 78

ProjectPro

OCTOBER 20, 2021

If you are unsure, be vocal about your thought process and the way you are thinking – take inspiration from the examples below and explain the answer to the interviewer through your learnings and experiences from data science and machine learning projects. It will explain what an instance of the best-in-class answers would sound like.

Machine Learning 52

Machine Learning Algorithm Government Data Science 52

ProjectPro

DECEMBER 10, 2021

This blog covers the top 50 most frequently asked Azure interview questions and answers. Well, this Azure interview questions and answers blog will help you land your dream cloud computing job role! A user only pays for the resources he needs from a cloud service provider and accesses them over a secure Internet connection.

BI 52

BI Cloud Computing SQL Database 52

ProjectPro

AUGUST 24, 2016

However, this blog post focuses on the need for HBase, which data structure is used in HBase, data model and the high level functioning of the components in the apache HBase architecture. If you need random access, you have to have HBase."- HBase provides real-time read or write access to data in HDFS.

Architecture 40

Architecture IT Hadoop NoSQL 40

ProjectPro

AUGUST 24, 2021

Data professionals who work with raw data like data engineers, data analysts, machine learning scientists , and machine learning engineers also play a crucial role in any data science project. And, out of these professions, this blog will discuss the data engineering job role.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52