Data Engineering Podcast

SEPTEMBER 16, 2018

What is unique about customer event data from an ingestion and processing perspective? Challenges with properly matching up data between sources Data collection is one of the more difficult aspects of an analytics pipeline because of the potential for inconsistency or incorrect information.

Google Cloud 100

Google Cloud Hadoop Business Intelligence Consulting 100

Knowledge Hut

NOVEMBER 28, 2023

As a Data Engineer, you must: Work with the uninterrupted flow of data between your server and your application. Work closely with software engineers and data scientists. Traditional data transformation tools are still relevant today, while next-generation Kafka, cloud-based tools, and SQL are on the rise for 2023.

Data Engineering 52

Data Engineering Data Engineer Engineering Generalist 52

Ascend.io

SEPTEMBER 14, 2023

Here are some examples of how Python can be applied to various facets of data engineering: Data Collection Web scraping has become an accessible task thanks to Python libraries like Beautiful Soup and Scrapy, empowering engineers to easily gather data from web pages.

Data Engineering 52

Data Engineering Data Engineer Python Engineering 52

Knowledge Hut

SEPTEMBER 25, 2023

In order to properly execute Data Analysis and come up with the optimal solution to a problem, you must have a solid background in mathematics and statistics. You should be able to effectively communicate with the prospective teams as a Data Analyst and present your results to them.

Certification 52

Certification Business Analyst Big Data Data Analysis 52

Knowledge Hut

JANUARY 22, 2024

Capstone projects involve analyzing company data to drive business strategy and decisions. Cloud Computing Cloud computing courses focus on deploying and managing big data platforms like Hadoop, Spark, Kafka etc on cloud infrastructure. Students work with SQL, NoSQL databases, Hadoop ecosystem, Spark, Kafka etc.

Data Science 52

Data Science Certification Education Data Lake 52

AltexSoft

FEBRUARY 11, 2023

It serves as a foundation for the entire data management strategy and consists of multiple components including data pipelines; , on-premises and cloud storage facilities – data lakes , data warehouses , data hubs ;, data streaming and Big Data analytics solutions ( Hadoop , Spark , Kafka , etc.);

Data Architect 87

Data Architect Certification Generalist Big Data 87

Knowledge Hut

DECEMBER 29, 2023

A Data Engineer is someone proficient in a variety of programming languages and frameworks, such as Python, SQL, Scala, Hadoop, Spark, etc. One of the primary focuses of a Data Engineer's work is on the Hadoop data lakes. NoSQL databases are often implemented as a component of data pipelines.

Data Science 98

Data Science Data Mining Deep Learning Programming Language 98

Knowledge Hut

MAY 9, 2024

They deploy and maintain database architectures, research new data acquisition opportunities, and maintain development standards. Average Annual Salary of Data Architect On average, a data architect makes $165,583 annually.

Data Science 52

Data Science Data Mining Data Architect Programming Language 52

Knowledge Hut

JANUARY 24, 2024

Pattern Recognition : Observing recurring trends or patterns within data to extract meaningful information. Tool Proficiency: Utilizing a diverse set of tools and technologies, including R, Tableau, Python, Matlab, Hive, Impala, PySpark, Excel, Hadoop, SQL, and SAS, to manipulate and analyze data efficiently.

Database-centric 52

Database-centric Data Science Machine Learning Datasets 52

ProjectPro

FEBRUARY 21, 2023

Knowledge of the definition and architecture of AWS Big Data services and their function in the data engineering lifecycle, including data collection and ingestion, data analytics, data storage, data warehousing, data processing, and data visualization.

Certification 52

Certification Data Engineering Data Engineer Engineering 52

Knowledge Hut

JANUARY 19, 2024

Within the curriculum for self-study, mastering time series analysis enables individuals to analyze and interpret data collected over time. Importance: Analyzes and interprets data collected over time. Enhances the ability to handle temporal aspects of data.

Data Science 52

Data Science Machine Learning Datasets Algorithm 52

Knowledge Hut

OCTOBER 27, 2023

Trending Open-Source Data Analytics Project Ideas Predictive Maintenance for Industrial Machinery - Develop a machine learning model to predict equipment failures based on sensor data collected from industrial machines. This can help prevent downtime and maintenance costs.

Data Analytics 52

Data Analytics Coding Project Medical 52

AltexSoft

JUNE 26, 2023

While today’s world abounds with data, gathering valuable information presents a lot of organizational and technical challenges, which we are going to address in this article. We’ll particularly explore data collection approaches and tools for analytics and machine learning projects. What is data collection?

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

Knowledge Hut

JANUARY 19, 2024

New Analytics Strategy vs. Existing Analytics Strategy Business Intelligence is concerned with aggregated data collected from various sources (like databases) and analyzed for insights about a business' performance. Tools Business intelligence uses various tools to collect, analyze, and report data.

Business Intelligence 52

Business Intelligence BI Business Analyst Aggregated Data 52

Knowledge Hut

JUNE 20, 2023

Additionally, they create and test the systems necessary to gather and process data for predictive modelling. Data engineers play three important roles: Generalist: With a key focus, data engineers often serve in small teams to complete end-to-end data collection, intake, and processing.

Machine Learning 52

Machine Learning Data Engineering Data Engineer Engineering 52

Grouparoo

OCTOBER 6, 2021

13 Column Names as Contracts Standardize columns names to minimize confusion 14 Consensual, Privacy-Aware Data Collection At some point does Grouparoo get properties noted as PII and what it means for a profile to opt out? 15 Cultivate Good Working Relationships with Data Consumers Practice empathy 16 Data Engineering !

Data Engineering 52

Data Engineering Data Engineer Engineering Pipeline-centric 52

ProjectPro

JUNE 9, 2021

Difference between Data Science and Data Engineering Data Science Data Engineering Data Science involves extracting information from raw data to derive business insights and values using statistical methods. Data Engineering is associated with data collecting, processing, analyzing, and cleaning data.

Data Engineering 52

Data Engineering Data Engineer Engineering Amazon Web Services 52

AltexSoft

MAY 27, 2022

A large hospital group partnered with Intel, the world’s leading chipmaker, and Cloudera, a Big Data platform built on Apache Hadoop , to create AI mechanisms predicting a discharge date at the time of admission. Intel and Cloudera saved a hospital system millions of dollars. Here are several popular options for LOS model development.

Hospitality 98

Hospitality Medical Healthcare Algorithm 98

ProjectPro

APRIL 17, 2015

Businesses are wading into the big data trends as they do not want to take the risk of being left behind. This articles explores four latest trends in big data analytics that are driving implementation of cutting edge technologies like Hadoop and NoSQL. billionby 2020, recording a CAGR of 35.1% during 2014 - 2020.

Big Data 52

Big Data Data Analysis NoSQL Deep Learning 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. What are its limitations and how do the Hadoop ecosystem address them? scalability.

Big Data Tools 98

Big Data Tools Hadoop Big Data Database-centric 98

Knowledge Hut

JANUARY 30, 2024

Audio Transcription: Audio data can be transcribed into text using speech recognition technology, enabling the extraction of spoken content for analysis, such as customer service call logs or voice recordings.

ETL Tools 52

ETL Tools Database-centric Data Mining Data Cleanse 52

Knowledge Hut

FEBRUARY 27, 2023

This highly technical position requires apt education, certification, tech, soft skills, and experience.

Data Engineering 52

Data Engineering Data Engineer Database-centric Pipeline-centric 52

ProjectPro

JUNE 2, 2015

This will supercharge the marketing tactics of the business and make data precious than ever. Before organizations rely on data driven decision making, it is important for them to have a good processing power like Hadoop in place for data processing. of marketers believe that they have the right big data talent.

Big Data 40

Big Data Hadoop Banking Retail 40

Knowledge Hut

DECEMBER 26, 2023

However, as we progressed, data became complicated, more unstructured, or, in most cases, semi-structured. This mainly happened because data that is collected in recent times is vast and the source of collection of such data is varied, for example, data collected from text files, financial documents, multimedia data, sensors, etc.

Data Engineering 98

Data Engineering Data Engineer Engineering Pipeline-centric 98

Knowledge Hut

NOVEMBER 15, 2023

Example 7: Individual with experience in statistical analysis and the ability to work on a wide array of data systems. Aiming to use my strong data science skills in a dynamic environment to enhance data collection procedures to positively impact the organization.

Finance 98

Finance Business Intelligence Database-centric Certification 98

Knowledge Hut

NOVEMBER 28, 2023

Not only will it help with your data science knowledge, but it will also improve your resume. Who is a Data Scientist? Data scientists are experts who find, collect and evaluate big data collections. Computer science, mathematics, and statistics training are often required for data science positions.

Data Science 52

Data Science Telecommunication Recruitment Finance 52

DareData

SEPTEMBER 11, 2020

Adding to that, there's a whole hype sensation that big companies might face - there's countless technologies, methodologies and innovations regarding data that come and go, most of them passing through a kind of funnel process that enables the surviving of the fittest (or the luckiest) - SQL stuck around, Hadoop not so.

Data Science 52

Data Science Algorithm Data Machine Learning 52

ProjectPro

MAY 8, 2015

Companies are using a VPN (Virtual Private Network) for collecting user data as customers entrust companies who are equipped with proper security measures. Transparency is the key to Success The frequently occurring high profile big data security breaches are enough to make cautious clients nervous about sharing their data.

Big Data 40

Big Data Retail Unstructured Data Banking 40

ProjectPro

NOVEMBER 7, 2016

Understanding the Hadoop architecture now gets easier! This blog will give you an indepth insight into the architecture of hadoop and its major components- HDFS, YARN, and MapReduce. We will also look at how each component in the Hadoop ecosystem plays a significant role in making Hadoop efficient for big data processing.

Hadoop 40

Hadoop Architecture IT Big Data 40

Knowledge Hut

MARCH 27, 2024

Real-time analytics platforms in big data apply logic and math to gain faster insights into data, resulting in a more streamlined and informed decision-making process. Some open-source technology for big data analytics are : Hadoop. Listed below are the top and the most popular tools for big data analytics : 1.

Big Data 52

Big Data Data Analytics MongoDB Big Data Tools 52

ProjectPro

MARCH 17, 2014

Big data and hadoop are catch-phrases these days in the tech media for describing the storage and processing of huge amounts of data. Over the years, big data has been defined in various ways and there is lots of confusion surrounding the terms big data and hadoop. What is Big Data according to IBM?

Hadoop 52

Hadoop Big Data Unstructured Data Retail 52

ProjectPro

AUGUST 21, 2015

With the help of ProjectPro’s Hadoop Instructors, we have put together a detailed list of big data Hadoop interview questions based on the different components of the Hadoop Ecosystem such as MapReduce, Hive, HBase, Pig, YARN, Flume, Sqoop , HDFS, etc. What is the difference between Hadoop and Traditional RDBMS?

Hadoop 40

Hadoop Big Data Metadata Java 40

ProjectPro

JANUARY 31, 2023

There are three steps involved in the deployment of a big data model: Data Ingestion: This is the first step in deploying a big data model - Data ingestion, i.e., extracting data from multiple data sources. How is Hadoop related to Big Data? Explain the difference between Hadoop and RDBMS.

Big Data 52

Big Data Hadoop AWS Relational Database 52

ProjectPro

SEPTEMBER 26, 2021

Big Data Engineers are professionals who handle large volumes of structured and unstructured data effectively. They are responsible for changing the design, development, and management of data pipelines while also managing the data sources for effective data collection.

Big Data 52

Big Data Data Engineering Data Engineer Engineering 52

Cloudera

DECEMBER 14, 2020

CDP is the next generation big data solution that manages and secures the end-to-end data lifecycle – collecting, enriching, processing, analyzing, and predicting with their streaming data – to drive actionable insights and data-driven decision making. Why upgrade to CDP now?

Process 69

Process Kafka Government Big Data 69

Knowledge Hut

FEBRUARY 7, 2023

SAS library Remote access for data sources such as Azure, SAS catalogue, Hadoop, S3, zip and more.  PROC Step: The PROC step instructs SAS on what analysis was conducted on the data, such as regression, analysis of variance, mean computation, and so on. PROCs can also do things like present information about SAS data collection.

Data Science 52

Data Science Datasets SQL Data Mining 52

U-Next

AUGUST 17, 2022

Hadoop Apache Data Engineers utilize the open-source Hadoop platform to store and process enormous volumes of data. Hadoop is a collection of tools that allow data integration rather than a single platform. Big Data analytics can benefit from it because of this. Conclusion.

Data Engineering 52

Data Engineering Data Engineer Pipeline-centric Database-centric 52