Data Engineering Weekly

MAY 5, 2024

The motivation for Machine Unlearning is critical from the privacy perspective and for model correction, fixing outdated knowledge, and access revocation of the training dataset. It’s an uphill battle for the data team if you end up in an organization where the executives don’t believe in data for the decision-making process.

Data Engineering 67

Data Engineering Data Engineer Engineering Google Cloud 67

Zalando Engineering

FEBRUARY 28, 2018

Apache’s lightning fast engine for data analysis and machine learning In recent years, there has been a massive shift in the industry towards data-oriented decision making backed by enormously large data sets. Problem As data is rapidly growing, we need a tool which can clean and train the data fast enough.

Data Analysis 40

Data Analysis Hadoop Datasets Scala 40

Knowledge Hut

DECEMBER 26, 2023

Of course, handling such huge amounts of data and using them to extract data-driven insights for any business is not an easy task; and this is where Data Science comes into the picture. These skills are essential to collect, clean, analyze, process and manage large amounts of data to find trends and patterns in the dataset.

Data Science 97

Data Science BI Business Intelligence Data Mining 97

Knowledge Hut

APRIL 23, 2024

Big data has revolutionized the world of data science altogether. With the help of big data analytics, we can gain insights from large datasets and reveal previously concealed patterns, trends, and correlations. Learn more about the 4 Vs of big data with examples by going for the Big Data certification online course.

Big Data 52

Big Data Media Datasets Unstructured Data 52

Knowledge Hut

JUNE 28, 2023

By examining these factors, organizations can make informed decisions on which approach best suits their data analysis and decision-making needs. Parameter Data Mining Business Intelligence (BI) Definition The process of uncovering patterns, relationships, and insights from extensive datasets.

Data Mining 52

Data Mining Business Intelligence BI Datasets 52

Knowledge Hut

JANUARY 30, 2024

In summary, data extraction is a fundamental step in data-driven decision-making and analytics, enabling the exploration and utilization of valuable insights within an organization's data ecosystem. What is the purpose of extracting data? The process of discovering patterns, trends, and insights within large datasets.

ETL Tools 52

ETL Tools Database-centric Data Mining Data Cleanse 52

Knowledge Hut

JANUARY 29, 2024

So, join us on this enlightening journey as we demystify Data Wrangling and reveal how it empowers businesses to harness the true potential of their data. What Is Data Wrangling? Data Wrangling, often referred to as Data Munging, is a fundamental process in the world of data analysis and management.

Raw Data 52

Raw Data Data Mining Data Preparation Structured Data 52

Knowledge Hut

DECEMBER 26, 2023

Python for Data Analysis By Wes McKinney Online Along with Machine Learning, you also need to learn about Python, a widely used programming language in the field of Data Analytics. Some of the best books that will guide you in R are as follows:_ R Cookbook: Proven Recipes for Data Analysis, Statistics, and Graphics (Author: J.

Data Science 52

Data Science Scala Programming Language R (Programming) 52

Edureka

AUGUST 2, 2023

Programming Languages for Data Scientists Here are the top 11 programming languages for data scientists, listed in no particular order: 1. Due to its strong data analysis and manipulation skills, it has significantly increased its prominence in the field of data science. Embark on Your Data Science Journey Today!

Programming Language 52

Programming Language Programming Scala Pharmaceutical 52

Knowledge Hut

JANUARY 19, 2024

Embracing data science isn't just about understanding numbers; it's about wielding the power to make impactful decisions. Imagine having the ability to extract meaningful insights from diverse datasets, being the architect of informed strategies that drive business success. That's the promise of a career in data science.

Data Science 52

Data Science Machine Learning Datasets Algorithm 52

Knowledge Hut

OCTOBER 30, 2023

Data Visualization: Assist in selecting appropriate visualizations for data presentation and formatting visuals for clarity and aesthetics. Data Analysis: Perform basic data analysis and calculations using DAX functions under the guidance of senior team members.

BI 52

BI Business Intelligence Data Cleanse Business Analyst 52

Knowledge Hut

DECEMBER 29, 2023

Data Mining Data science field of study, data mining is the practice of applying certain approaches to data in order to get useful information from it, which may then be used by a company to make informed choices. It separates the hidden links and patterns in the data. Data mining's usefulness varies per sector.

Data Science 98

Data Science Data Mining Deep Learning Programming Language 98

Monte Carlo

FEBRUARY 27, 2024

Right now, RAG is the essential technique to make GenAI models useful by giving an LLM access to an integrated, dynamic dataset while responding to prompts. But instead of integrating a dynamic database to an existing LLM, fine-tuning involves training an LLM on a smaller, task-specific, and labeled dataset.

Data Engineering 59

Data Engineering Data Engineer Engineering High Quality Data 59

Knowledge Hut

NOVEMBER 3, 2023

MongoDB’s unique architecture and features have secured it a place uniquely in data scientists’ toolboxes globally. With large amounts of unstructured data requiring storage and many popular data analysis tools working well with MongoDB, the prospects of picking it as your next database can be very enticing.

MongoDB 52

MongoDB Data Science NoSQL ETL Tools 52

Knowledge Hut

DECEMBER 21, 2023

Hadoop helps in data mining, predictive analytics, and ML applications. Why are Hadoop Big Data Tools Needed? With the help of Hadoop big data tools, organizations can make decisions that will be based on the analysis of multiple datasets and variables, and not just small samples or anecdotal incidents.

Hadoop 52

Hadoop Big Data NoSQL Unstructured Data 52

Edureka

FEBRUARY 8, 2024

In-Memory Caching- Memory-optimized instances are suitable for in-memory caching solutions, enhancing the speed of data access. Big Data Processing- Workloads involving large datasets, analytics, and data processing can benefit from the enhanced memory capacity provided by M-Series instances.

AWS 52

AWS NoSQL Deep Learning Datasets 52

AltexSoft

AUGUST 29, 2023

Data sources can be broadly classified into three categories. Structured data sources. These are the most organized forms of data, often originating from relational databases and tables where the structure is clearly defined. Semi-structured data sources. Exploratory data analysis (EDA).

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

Ascend.io

NOVEMBER 21, 2023

Extract The initial stage of the ELT process is the extraction of data from various source systems. This phase involves collecting raw data from the sources, which can range from structured data in SQL or NoSQL servers, CRM and ERP systems, to unstructured data from text files, emails, and web pages.

Raw Data 52

Raw Data Data Warehouse Data Cleanse Data Integration 52

Workfall

JULY 4, 2023

In this blog, we will cover: DBT Overview Snowflake Overview DBT With Snowflake Hands-On Understanding DBT Project Structure Creating Your First Model Conclusion DBT Overview In the magical world of DBT, there are three key concepts that bring order and clarity to the realm of data: models, transformations, and tests.

Data Warehouse 69

Data Warehouse SQL PostgreSQL Database 69

phData: Data Engineering

SEPTEMBER 19, 2023

With the amounts of data involved, this can be crucial to utilizing a data lake effectively. Metadata Management can be performed manually by creating spreadsheets and documents notating information about the various datasets. However, this can be time-consuming and prone to human error, leading to misinformation.

Data Lake 52

Data Lake Process Metadata Data Warehouse 52

Knowledge Hut

NOVEMBER 16, 2023

What distinguishes Generative AI is its capacity to learn from current data and then generate entirely new and realistic outputs that reflect the essence of what it has learned. This can significantly speed up the research process and allow scientists to focus on analysis rather than report writing.

Medical 52

Medical Healthcare Hospitality Entertainment 52

ProjectPro

OCTOBER 18, 2021

Datasets like Google Local, Amazon product reviews, MovieLens, Goodreads, NES, Librarything are preferable for creating recommendation engines using machine learning models. They have a well-researched collection of data such as ratings, reviews, timestamps, price, category information, customer likes, and dislikes.

Machine Learning 52

Machine Learning Project Datasets Algorithm 52

AltexSoft

MARCH 28, 2022

Negotiate a proprietary agreement with Airbnb, authorizing you to use their data. Publicly available datasets. Download free, anonymized datasets from Inside Airbnb , a non-commercial platform that presents snapshots of Airbnb listings with reviews, calendar and over 50 data points (pieces of information describing the listing.).

Hospitality 52

Hospitality Business Intelligence Datasets Machine Learning 52

ProjectPro

DECEMBER 7, 2021

It can also consist of simple or advanced processes like ETL (Extract, Transform and Load) or handle training datasets in machine learning applications. In broader terms, two types of data -- structured and unstructured data -- flow through a data pipeline. Step 1- Automating the Lakehouse's data intake.

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 52

Knowledge Hut

JUNE 19, 2023

Businesses use various data visualization techniques to present information from structured, semi-structured, or unstructured data collections. The amount of data is increasing every day, and organizations need better management to handle it. Business intelligence is the key to dealing with enormous datasets.

Business Intelligence 52

Business Intelligence BI Programming Language Recruitment 52

Knowledge Hut

MAY 2, 2024

To store and process even only a fraction of this amount of data, we need Big Data frameworks as traditional Databases would not be able to store so much data nor traditional processing systems would be able to process this data quickly. collect(): Return all the elements of the dataset as an array at the driver program.

Scala 94

Scala Hadoop Datasets Java 94

ProjectPro

NOVEMBER 14, 2015

These Apache Hadoop projects are mostly into migration, integration, scalability, data analytics, and streaming analysis. These Apache Spark projects are mostly into link prediction, cloud hosting, data analysis, and speech analysis. Data Integration 3.Scalability Specialized Data Analytics 7.Streaming

Hadoop 52

Hadoop Project Big Data Healthcare 52

ProjectPro

JULY 13, 2015

Large commercial banks like JPMorgan have millions of customers but can now operate effectively-thanks to big data analytics leveraged on increasing number of unstructured and structured data sets using the open source framework - Hadoop.

Hadoop 52

Hadoop Big Data Data Analytics Banking 52

ProjectPro

FEBRUARY 16, 2023

For example, the data manipulation language (DML) and data definition language (DDL) allow engineers to collect and manipulate data scripts and design and modify data structures. To analyze big data and create data lakes and data warehouses , SQL-on-Hadoop engines run on top of distributed file systems.

Data Engineering 52

Data Engineering Data Engineer SQL Engineering 52

ProjectPro

OCTOBER 15, 2014

Generally data to be stored in the database is categorized into 3 types namely Structured Data, Semi Structured Data and Unstructured Data. 2) Hive Hadoop Component is used for completely structured Data whereas Pig Hadoop Component is used for semi structured data.

Hadoop 52

Hadoop Unstructured Data Java SQL 52

Knowledge Hut

SEPTEMBER 26, 2023

Power BI Basics Microsoft Power BI is a business intelligence and data visualization software that is used to create interactive dashboards and business intelligence reports from various data sources. Dashboards, reports, workspace, datasets, and apps are the building blocks of power BI.

BI 52

BI Business Intelligence Raw Data Data Analysis 52

ProjectPro

JULY 22, 2016

Data warehouses do a good job for what they are meant to do, but with disparate data sources and different data types like transaction logs, social media data, tweets, user reviews, and clickstream data –Data Lakes fulfil a critical need. Data Warehouses do not retain all data whereas Data Lakes do.

Data Lake 40

Data Lake Data Warehouse Hadoop Unstructured Data 40

Knowledge Hut

SEPTEMBER 26, 2023

Whether you're running ad-hoc queries or performing complex data transformations, Azure Synapse ensures that your analytics are conducted swiftly, enabling timely decision-making. It supports a variety of query languages, including the industry-standard SQL, as well as popular data analysis languages like Python and R.

Data Lake 52

Data Lake Database-centric Pipeline-centric Machine Learning 52

ProjectPro

JANUARY 25, 2022

One of the most in-demand technical skills these days is analyzing large data sets, and Apache Spark and Python are two of the most widely used technologies to do this. Python is one of the most extensively used programming languages for Data Analysis, Machine Learning , and data science tasks.

Big Data 52

Big Data Data Process Process Kafka 52

Edureka

JANUARY 18, 2024

Need for Data Science Data scientists play a vital part in improving decision-making, increasing business efficiency, and turning massive volumes of data into actionable insights. They manage intricate datasets, create forecasting models, and examine consumer behavior to deliver tailored experiences.

Data Science 40

Data Science Deep Learning NoSQL Machine Learning 40

Knowledge Hut

DECEMBER 26, 2023

If we look at history, the data that was generated earlier was primarily structured and small in its outlook. A simple usage of Business Intelligence (BI) would be enough to analyze such datasets. However, as we progressed, data became complicated, more unstructured, or, in most cases, semi-structured.

Data Engineering 98

Data Engineering Data Engineer Engineering Pipeline-centric 98

Edureka

AUGUST 2, 2023

They are responsible for processing, cleaning, and transforming raw data into a structured and usable format for further analysis or integration into databases or data systems. Their efforts make ensuring that data is accurate, dependable, and consistent, laying the groundwork for data analysis and decision-making.

Data Process 52

Data Process Process Data Cleanse Data Mining 52