ProjectPro

JUNE 6, 2025

Data Lake vs Data Warehouse - The Differences Before we closely analyse some of the key differences between a data lake and a data warehouse, it is important to have an in depth understanding of what a data warehouse and data lake is. Data Lake vs Data Warehouse - The Introduction What is a Data warehouse?

Data Lake 40

Data Lake Data Warehouse Cloud Hadoop 40

databricks

APRIL 30, 2025

SQL has been the lingua franca for structured data analysis for multiple decades, and we have done a lot of work in the last few

SQL 112

SQL Structured Data Data Analysis Data 112

ProjectPro

JUNE 6, 2025

Data engineering is the foundation for data science and analytics by integrating in-depth knowledge of data technology, reliable data governance and security, and a solid grasp of data processing. Data engineers need to meet various requirements to build data pipelines.

AWS 52

AWS Data Engineer Data Engineering Project 52

ProjectPro

JUNE 6, 2025

The term "intelligence" in AI refers to computer intelligence, whereas "intelligence" in BI refers to more intelligent business decision-making that data analysis and visualization may provide. AI can help BI tools provide clear, actionable insights from the study data. Individual data analysis takes a long time.

Business Intelligence 56

Business Intelligence BI Data Mining Raw Data 56

ProjectPro

JUNE 6, 2025

Data integration with ETL has evolved from structured data stores with high computing costs to natural state storage with read operation alterations thanks to the agility of the cloud. Data integration with ETL has changed in the last three decades. Simply set up AWS Glue to point to the data kept in AWS.

AWS 40

AWS Data Management ETL Tools Management 40

ProjectPro

JUNE 6, 2025

However, the vast volume of data will overwhelm you if you start looking at historical trends. The time-consuming method of data collection and transformation can be eliminated using ETL. You can analyze and optimize your investment strategy using high-quality structured data.

BI 45

BI ETL Tools Retail Healthcare 45

ProjectPro

JUNE 6, 2025

Are you struggling to adapt data analysis techniques? Look no further than Pandas Functions to streamline your efforts and advance your skills in data manipulation. Its cornerstone is the versatile DataFrame structure, which simplifies structured data handling.

Python 40

Python Datasets Data Analysis Data Science 40

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. Summary In this article, we covered how Spark can be optimized for data analysis and machine learning.

Data Analysis 40

Data Analysis Hadoop Transportation SQL 40

ProjectPro

JUNE 6, 2025

Azure Tables: NoSQL storage for storing structured data without a schema. The Data Lake Store, the Analytics Service, and the U-SQL programming language are the three key components of Azure Data Lake Analytics. You can quickly process and analyze enormous amounts of data due to the combination of SQL and C#.

Data Lake 40

Data Lake Amazon Web Services Data Warehouse SQL 40

ProjectPro

JUNE 6, 2025

Redshift Project for Data Analysis with Amazon Quicksight 2.Amazon Using Airflow for Building and Monitoring the Data Pipeline of Amazon Redshift 4. Redshift Project for Data Analysis with Amazon Quicksight Today, businesses generate a massive amount of structured and unstructured data from their business operations.

Data Pipeline 64

Data Pipeline AWS Project Building 64

ProjectPro

JUNE 6, 2025

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 40

Big Data Data Process Process Kafka 40

Data Engineering Weekly

MARCH 5, 2025

Start the Data Governance Process: Don't wait until the last minute to build the data governance framework. The Catalog Conundrum: Beyond Structured Data The role of the catalog is evolving. Initially, catalogs focused on managing metadata for structured data in Iceberg tables.

Hadoop 57

Hadoop Metadata Data Ingestion Data Governance 57

ProjectPro

JUNE 6, 2025

Source- Streaming Data Pipeline using Spark, HBase, and Phoenix Project Real-time Data Ingestion Example Using Flume And Spark You should also check out this real-time Twitter data analysis project using Flume and Kafka. This approach is ideal for applications that require low latency and continuous data analysis.

Data Ingestion 40

Data Ingestion Kafka Google Cloud AWS 40

ProjectPro

JUNE 6, 2025

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 40

ETL Tools Hadoop Relational Database Unstructured Data 40

KDnuggets

MAY 1, 2025

DuckDB lets you run SQL queries on JSON files, making structured and semi-structured data analysis a breeze. Tired of wrangling JSON with scripts and regex?

SQL 79

SQL Structured Data Data Analysis Data 79

ProjectPro

JUNE 6, 2025

Step 3: Developing Your Generative AI Solution Once you’ve gathered your training data and selected the appropriate frameworks, it’s time to start developing your generative AI model. This involves: Model Design- Choose the right architecture—GANs for images, VAEs for structured data.

Building 52

Building Banking SQL Deep Learning 52

ProjectPro

JUNE 6, 2025

The Report Writer then synthesizes insights into a structured report. Source Code: How to Build an LLM-Powered Data Analysis Agent? These agents can ingest financial reports in PDF format, extract relevant data, and provide real-time insights on revenue changes, profitability, and market performance.

Project 59

Project Building Banking Healthcare 59

ProjectPro

JUNE 6, 2025

Semi-Structured Snowflake Data Types Since data can not always be arranged within tables in rows and columns, Snowflake provides data types for handling such semi-structured data. Semi-structured datatypes offer more flexibility for querying and storing data.

Bytes 40

Bytes Data Unstructured Data Structured Data 40

ProjectPro

JUNE 6, 2025

So, have you been wondering what happens to all the data collected from different sources, logs on your machine, data generated from your mobile, data in databases, customer data, and so on? We can do a lot of data analysis and produce visualizations to deliver value from these data sources.

Data Science 40

Data Science Data Engineer Data Engineering Engineering 40

ProjectPro

JUNE 6, 2025

It is helpful for data analysis and manipulation tasks in Data Science and is ideal for dealing with numerical tables and data in time series. The Pandas library has flexible data structures that allow for efficient data manipulation and make it easier to represent data, improving data analysis.

Data Science 40

Data Science Hadoop Unstructured Data Machine Learning 40

ProjectPro

JUNE 6, 2025

Features of Snowflake Highly Scalable- Users can establish an almost infinite range of virtual warehouses, each of which runs its task using the data in its database. Data engineers use Power BI to generate dynamic visualizations by processing data sets into live dashboards and analysis insights.

Data Engineer 45

Data Engineer Data Engineering Engineering Kafka 45

Analytics Vidhya

JANUARY 31, 2023

But are they still useful without the data? The machine learning algorithms heavily rely on data that we feed to them. The quality of data we feed to the algorithms […] The post Practicing Machine Learning with Imbalanced Dataset appeared first on Analytics Vidhya. The answer is No.

Machine Learning 241

Machine Learning Datasets Algorithm Structured Data 241

ProjectPro

JUNE 6, 2025

Ready to take your big data analysis to the next level? Check out this comprehensive tutorial on Business Intelligence on Hadoop and unlock the full potential of your data! million terabytes of data are generated daily. Both structured and unstructured data in distributed file systems.

BI 40

BI Hadoop Big Data Business Intelligence 40

ProjectPro

JUNE 6, 2025

It will also cover a step-by-step Google BigQuery tutorial to help you get started with your data warehousing solutions. Google BigQuery Data Analysis Workflows Google BigQuery Architecture- A Detailed Overview Google BigQuery Datatypes BigQuery Tutorial for Beginners: How To Use BigQuery? What is Google BigQuery Used for?

Bytes 40

Bytes Google Cloud Data Warehouse Cloud Storage 40

Snowflake

MAY 8, 2025

Snowflake Cortex AI Snowflake Cortex AI is a suite of integrated features and services that include fully managed LLM inference, fine-tuning and RAG for structured and unstructured data, so that customers can quickly analyze unstructured data alongside their structured data and expedite the building of AI apps.

Unstructured Data 98

Unstructured Data Government Coding Structured Data 98

ProjectPro

JUNE 6, 2025

The data engineer skill of building data warehousing solutions expects a data engineer to curate data and perform data analysis on that data from multiple sources to support the decision-making process. In such instances, raw data is available in the form of JSON documents, key-value pairs, etc.,

Data Engineer 49

Data Engineer Data Engineering Engineering Hadoop 49

ProjectPro

JUNE 6, 2025

In this tutorial, we’ll walk through the process of custom AI agent development in LangChain for health data analysis. Specifically, you’ll explore how AI can assist diagnostics and patient care by building an AI agent that fetches blood glucose data and provides insightful recommendations.

Building 40

Building Banking Data Analysis Healthcare 40

Knowledge Hut

FEBRUARY 29, 2024

Get to know more about data science for business. Learning Data Analysis in Excel Data analysis is a process of inspecting, cleaning, transforming and modelling data with an objective of uncover the useful knowledge, results and supporting decision. In data analysis, EDA performs an important role.

Data Science 98

Data Science Database Design Machine Learning Datasets 98

ProjectPro

JUNE 6, 2025

Step 4: Advanced PySpark Concepts Once you're comfortable with the basics, it's time to explore more advanced topics: Spark SQL: Learn how to write SQL queries using Spark SQL, which allows you to interact with structured data seamlessly. Start with simple data analysis tasks and gradually take on more complex challenges.

Big Data 40

Big Data Python Machine Learning SQL 40

ProjectPro

JUNE 6, 2025

It is like a central location where quality data from multiple databases are stored. Data warehouses typically function based on OLAP (Online Analytical Processing) and contain structured and semi-structured data from transactional systems, operational databases, and other data sources.

Data Warehouse 40

Data Warehouse Data Mining Google Cloud PostgreSQL 40

ProjectPro

JUNE 6, 2025

In broader terms, two types of data -- structured and unstructured data -- flow through a data pipeline. The structured data comprises data that can be saved and retrieved in a fixed format, like email addresses, locations, or phone numbers. Step 1- Automating the Lakehouse's data intake.

Data Pipeline 40

Data Pipeline Architecture Kafka Data Lake 40

ProjectPro

JUNE 6, 2025

Graph-based data gives a richer picture, showing how things are connected in a more detailed way. Before diving into the deets of GNNs, let us explore the graph structured data. A graph is a fundamental data structure used to represent relationships or connections between entities. What is a Graph?

Datasets 40

Datasets Medical Structured Data Food 40

ProjectPro

JUNE 6, 2025

Transform unstructured data into structured data by fixing errors, redundancies, missing numbers, and other anomalies, eliminating unnecessary data, optimizing data systems, and finding relevant insights. Data Analysis Data analysis is one of the essential skills every data modeler must possess.

NoSQL 40

NoSQL ETL Tools Certification SQL 40

ProjectPro

JUNE 6, 2025

Top 5 Benefits of Using a Python Machine Learning Library List of Top 10 Python Machine Learning Libraries NumPy (Numerical Python) Pandas SciPy Matplotlib Scikit-learn TensorFlow Keras PyTorch Seaborn OpenCV Master Data Science and Machine Learning with ProjectPro FAQs on Python ML Libraries What are Python Machine Learning Libraries?

Machine Learning 40

Machine Learning Python Deep Learning Algorithm 40

ProjectPro

JUNE 6, 2025

Data Variety Hadoop stores structured, semi-structured and unstructured data. RDBMS stores structured data. Data storage Hadoop stores large data sets. RDBMS stores the average amount of data. Works with only structured data. Hardware Hadoop uses commodity hardware.

Big Data 40

Big Data Hadoop Relational Database NoSQL 40

ProjectPro

JUNE 6, 2025

Storage, Processing, & Analytics Following data collection, the stored data undergoes a series of transformative processes to prepare it for analysis. Based on scalability, performance, and data structure, data is stored in suitable storage systems, such as relational databases, NoSQL databases, or data lakes.

Data Science 40

Data Science Building AWS Data Lake 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. To make accurate conclusions based on the analysis of the data, you need to understand what that data represents in the first place.

Data Science 97

Data Science BI Data Mining Business Intelligence 97