ProjectPro

JUNE 6, 2025

In this data warehousing project, you'll learn how to create a system that can determine whether or not a patient has heart disease. The data warehouse assists in correlating clinical and financial records to estimate the cost-effectiveness of care. Lastly, Google Data Studio is used to visualize the data.

Data Warehouse 40

Data Warehouse Coding Project Google Cloud 40

ProjectPro

JUNE 6, 2025

Additionally, using python programming for data engineering is an excellent approach to understanding the requirements of data scientists better. Python also helps data engineers to build efficient data pipelines as many data engineering tools use Python in the backend.

Data Engineering 40

Data Engineering Data Engineer Python Engineering 40

ProjectPro

JUNE 6, 2025

On the other hand, Data Engineering is all about efficient data management. Data engineers deal with tasks that involve designing and maintaining architectures, building robust data pipelines, understanding data warehouse architectures, and optimizing database systems using tools like Apache Hadoop , and Spark.

Data Science 52

Data Science Portfolio Programming Language Data 52

ProjectPro

JUNE 6, 2025

A professional data engineer designs systems to gather and navigate data. Data engineers require strong experience with multiple data storage technologies and frameworks to build data pipelines. A GCP data engineer is responsible for applying data engineering concepts through the Google Cloud Platform.

Data Engineering 40

Data Engineering Data Engineer Google Cloud Engineering 40

Knowledge Hut

DECEMBER 29, 2023

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 engineers may choose from a variety of career paths, including those of Database Developer, Data Engineer, etc.

Data Science 98

Data Science Data Mining Deep Learning Programming Language 98

ProjectPro

JUNE 6, 2025

Upskill yourself for your dream job with industry-level big data projects with source code. Business Intelligence Engineer Skills Business intelligence engineers employ their technical expertise to create and implement data warehouses, ETL procedures, and data mining models.

Business Intelligence 40

Business Intelligence Engineering BI Data Warehouse 40

Knowledge Hut

DECEMBER 26, 2023

They should know SQL queries, SQL Server Reporting Services (SSRS), and SQL Server Integration Services (SSIS) and a background in Data Mining and Data Warehouse Design. Data Architects, or Big Data Engineers, ensure the data availability and quality for Data Scientists and Data Analysts.

Data Science 97

Data Science BI Data Mining Business Intelligence 97

ProjectPro

JUNE 6, 2025

Keep in mind that a hiring manager prefers applicants who have experience building data pipelines using raw datasets rather than organized ones. For a data engineer, technical skills should include computer science, database technologies, programming languages, data mining tools, etc.

Data Engineering 40

Data Engineering Data Engineer Recruitment Engineering 40

ProjectPro

JUNE 6, 2025

mllib.fpm- Frequent Pattern Matching has been an important topic in data mining research for years now. Frequent pattern matching is often among the initial steps in analyzing a large-scale dataset, mining recurring items, itemsets, subsequences, or other components.

Big Data 40

Big Data Data Process Process Kafka 40

Knowledge Hut

JANUARY 18, 2024

They also look into implementing methods that improve data readability and quality, along with developing and testing architectures that enable data extraction and transformation. Skills along the lines of Data Mining, Data Warehousing, Math and statistics, and Data Visualization tools that enable storytelling.

Data Science 98

Data Science Deep Learning Business Analyst Data Mining 98

ProjectPro

JUNE 6, 2025

Among these are tools for general data manipulation like Pandas and specialized frameworks like PsychoPy. Python's three most common applications for data analysis include data mining , data processing, modeling, and visualization.

Data Analysis Tools 45

Data Analysis Tools Data Analysis BI R (Programming) 45

Towards Data Science

FEBRUARY 2, 2024

Time to build and maintain  — The time it takes to build and maintain your key data assets, including data products and machine learning capabilities, is a key lever that measures your data team’s productivity. Time to insight (or action)  — This lever is focused on the time it takes your data consumers to realize value.

Data 98

Data Aggregated Data Data Mining Machine Learning 98

Knowledge Hut

NOVEMBER 28, 2023

Let us take a look at the top technical skills that are required by a data engineer first: A. Technical Data Engineer Skills 1.Python Python is ubiquitous, which you can use in the backends, streamline data processing, learn how to build effective data architectures, and maintain large data systems.

Data Engineering 52

Data Engineering Data Engineer Engineering Generalist 52

ProjectPro

JUNE 6, 2025

Analysis Layer: The analysis layer supports access to the integrated data to meet its business requirements. The data may be accessed to issue reports or to find any hidden patterns in the data. Data mining may be applied to data to dynamically analyze the information or simulate and analyze hypothetical business scenarios.

Data Lake 40

Data Lake Data Warehouse Cloud Hadoop 40

Knowledge Hut

MARCH 7, 2024

Therefore, you can rest confident that our recommended software is reliable and potent enough to help you extract value from your data, whether you have your data pipeline and warehouse or are employing big data analytics providers. Importance of Big Data Analytics Tools Using Big Data Analytics has a lot of benefits.

Big Data 52

Big Data Data Analytics Data Mining MongoDB 52

Knowledge Hut

DECEMBER 22, 2023

Data analytics, data mining, artificial intelligence, machine learning, deep learning, and other related matters are all included under the collective term "data science" When it comes to data science, it is one of the industries with the fastest growth in terms of income potential and career opportunities.

Hadoop 98

Hadoop Deep Learning Machine Learning Data Science 98

ProjectPro

JUNE 6, 2025

Uses data science techniques to analyze data and build machine learning models. Handles the technical aspects of data science, such as data storage, data pipelines , and data security. Focuses on the analytical aspects of data science, such as data mining , ML, and statistical analysis.

Machine Learning 40

Machine Learning Certification Data Science Raw Data 40

ProjectPro

JUNE 6, 2025

Cristiano Breuel , Senior AI Manager at Nubank, defines the role of a data scientist in one of his articles- Data Scientist: Roles and Responsibilities Here are some of the key responsibilities of a Data Scientist- Data Wrangling and Cleaning- Collect, clean, and prepare data from various sources for analysis.

Machine Learning 40

Machine Learning Consulting Computer Science Software Engineering 40

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. They manage data storage and the ETL process. It may go as high as $211,000!

Data Science 52

Data Science Data Architect Data Mining Programming Language 52

DataKitchen

OCTOBER 11, 2021

The biggest challenge is broken data pipelines due to highly manual processes. Figure 1 shows a manually executed data analytics pipeline. The data engineer then emails the BI Team, who refreshes a Tableau dashboard. Figure 1: Example data pipeline with manual processes.

Engineering 60

Engineering Business Analyst BI Metadata 60

Edureka

FEBRUARY 9, 2023

Certified Azure Data Engineers are frequently hired by businesses to convert unstructured data into useful, structured data that data analysts and data scientists can use. Emerging Jobs Report, data engineer roles are growing at a 35 percent annual rate. What does an Azure Data Engineer Do?

Data Engineering 52

Data Engineering Data Engineer Engineering Data Mining 52

ProjectPro

JUNE 6, 2025

Companies frequently hire certified Azure Data Engineers to convert unstructured data into useful, structured data that data analysts and data scientists can use. Data infrastructure, data warehousing, data mining, data modeling, etc.,

Data Engineering 49

Data Engineering Data Engineer Engineering Certification 49

Knowledge Hut

DECEMBER 26, 2023

Trend analysis in data science is a technical analysis technique that attempts to forecast future stock price movements using recently observed trend data. Scalability in Artificial Intelligence Today's businesses have a confluence of statistics, systems architecture, machine learning deployments, and data mining.

Data Science 52

Data Science Database-centric Pipeline-centric Data Mining 52

Knowledge Hut

NOVEMBER 17, 2023

The job of an Azure Data Engineer is really needed in the world of handling and studying data. As Azure Data Engineers, they'll be responsible for creating and looking after solutions that use data to help the company. In the United States, the average Microsoft-certified Azure Data Engineer associate salary is $130,982.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Lake 52

ProjectPro

FEBRUARY 8, 2023

Apache Kafka is the most widely used open-source stream-processing solution for gathering, processing, storing, and analyzing large amounts of data. The platform has many benefits, including building data pipelines , using real-time data streams, supporting operational analytics, and integrating data from various sources.

Kafka 52

Kafka Banking Healthcare Medical 52

Knowledge Hut

DECEMBER 26, 2023

Mining of Massive Datasets By Jure Leskovec, Anand Rajaraman, Jeff Ullma This book will provide a comprehensive understanding of large-scale data mining and network analysis. Web Scraping Web scraping knowledge is one of the basic requirements to become a data scientist or analyst to develop completely automated systems.

Data Science 52

Data Science Scala Programming Language R (Programming) 52

Silectis

JANUARY 3, 2021

Data Engineering Data engineering is a process by which data engineers make data useful. Data engineers design, build, and maintain data pipelines that transform data from a raw state to a useful one, ready for analysis or data science modeling.

Data Engineering 40

Data Engineering Data Engineer Engineering Non-relational Database 40

Knowledge Hut

APRIL 19, 2023

Identify source systems and potential problems such as data quality, data volume, or compatibility issues. Step 2: Extract data: extracts the necessary data from the source system. This API may include using SQL queries or other data mining tools. It can handle huge data and is highly scalable.

Data Warehouse 52

Data Warehouse Business Intelligence ETL Tools Amazon Web Services 52

ProjectPro

JUNE 6, 2025

Data Analyst Career Path - Analytic Skills You Must Hone The first step in data analytics involves acquiring the essential skills and expertise for the specific job role. Data analysts mainly collect raw data from various data sets or databases and perform data mining and wrangling processes.

Consulting 40

Consulting Healthcare Programming Language BI 40

ProjectPro

JANUARY 19, 2022

Companies frequently hire certified Azure Data Engineers to convert unstructured data into useful, structured data that data analysts and data scientists can use. Data infrastructure, data warehousing, data mining, data modeling, etc.,

Data Engineering 52

Data Engineering Data Engineer Engineering Certification 52

Knowledge Hut

MARCH 27, 2024

Qubole Using ad-hoc analysis in machine learning, it fetches data from a value chain using open-source technology for big data analytics. Qubole provides end-to-end services in moving data pipelines with reduced time and effort. Multi-source data can be migrated to one location through this tool.

Big Data 52

Big Data Data Analytics MongoDB Big Data Tools 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

Knowledge Hut

MAY 23, 2024

KNIME: KNIME is another widely used open-source and free data science tool that helps in data reporting, data analysis, and data mining. With this tool, data science professionals can quickly extract and transform data.

Data Science 52

Data Science MongoDB Programming Language Data Mining 52

Databand.ai

DECEMBER 20, 2022

He has also completed courses in data analysis, applied data science, data visualization, data mining, and machine learning. Eric is active on GitHub and LinkedIn, where he posts about data analytics, data science, and Python.

Data Analytics 52

Data Analytics Google Cloud Data Mining Consulting 52

ProjectPro

MARCH 14, 2014

Online FM Music 100 nodes, 8 TB storage Calculation of charts and data testing 16 IMVU Social Games Clusters up to 4 m1.large Hadoop is used at eBay for Search Optimization and Research. 12 Cognizant IT Consulting Per client requirements Client projects in finance, telecom and retail.

Hadoop 40

Hadoop Big Data Data Mining Consulting 40

Knowledge Hut

DECEMBER 21, 2023

In this article, we will understand the promising data engineer career outlook and what it takes to succeed in this role. What is Data Engineering? Data engineering is the method to collect, process, validate and store data. It involves building and maintaining data pipelines, databases, and data warehouses.

Data Engineering 52

Data Engineering Data Engineer Engineering MongoDB 52

Knowledge Hut

JANUARY 30, 2024

However, through data extraction, this hypothetical mortgage company can extract additional value from an existing business process by creating a lead list, thereby increasing their chances of converting more leads into clients. Transformation: Once the data has been successfully extracted, it enters the refinement phase.

Database-centric 52

Database-centric ETL Tools Data Mining Data Cleanse 52