Towards Data Science

JANUARY 16, 2024

The concept of `Data Marts` was introduced. Image by the author 2004 to 2010 — The elephant enters the room New wave of applications emerged — Social Media, Software observability, etc. New data formats emerged — JSON, Avro, Parquet, XML etc. Result: Hadoop & NoSQL frameworks emerged. So what was missing?

Data Warehouse 95

Data Warehouse Data Architecture Relational Database NoSQL 95

Data Engineering Podcast

FEBRUARY 9, 2020

We have partnered with organizations such as O’Reilly Media, Corinium Global Intelligence, ODSC, and Data Council. Upcoming events include the Software Architecture Conference in NYC, Strata Data in San Jose, and PyCon US in Pittsburgh. Is there any utility in data vault modeling in a data lake context (S3, Hadoop, etc.)?

Data Lake 100

Data Lake Data Warehouse Hadoop NoSQL 100

ProjectPro

JUNE 6, 2025

A data warehouse is a relational database that has been technologically enhanced for accessing, storing, and querying massive amounts of data. Traditionally, engineers could store only structured data in data warehouses. Modern data warehouses can, however, combine both structured and unstructured data.

Data Science 40

Data Science Data Engineering Data Engineer Engineering 40

ProjectPro

JUNE 6, 2025

This means that a data warehouse is a collection of technologies and components that are used to store data for some strategic use. Data is collected and stored in data warehouses from multiple sources to provide insights into business data. Data from data warehouses is queried using SQL.

Data Lake 40

Data Lake Data Warehouse Cloud Hadoop 40

ProjectPro

JUNE 6, 2025

Project Idea : Build a data engineering pipeline to ingest and transform data, focusing on runs, wickets, and strike rates. Use the ESPNcricinfo Ball-by-Ball Dataset to process match data. Store raw data in AWS S3, preprocess it using AWS Lambda, and query structured data in Amazon Athena.

Data Engineering 59

Data Engineering Data Engineer Project Engineering 59

ProjectPro

JUNE 6, 2025

This architecture typically consists of several layers, each serving a specific purpose in handling and processing data instantaneously- Source- Microsoft Azure Official Documentation Data Ingestion Layer At the forefront of the architecture, this layer is responsible for the initial acquisition and ingestion of data streams from diverse sources.

Data Ingestion 40

Data Ingestion Kafka Google Cloud AWS 40

AltexSoft

MAY 14, 2021

To understand Big Data, you need to get acquainted with its attributes known as the four V’s: Volume is what hides in the “big” part of Big Data. This relates to terabytes to petabytes of information coming from a range of sources such as IoT devices, social media, text files, business transactions, etc. NoSQL databases.

Big Data 78

Big Data Data Analytics IT NoSQL 78

AltexSoft

MAY 12, 2023

Definition and examples Unstructured data , in its simplest form, refers to any data that does not have a pre-defined structure or organization. Unlike structured data, which is organized into neat rows and columns within a database, unstructured data is an unsorted and vast information collection.

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

ProjectPro

JUNE 6, 2025

With SQL, machine learning, real-time data streaming, graph processing, and other features, this leads to incredibly rapid big data processing. DataFrames are used by Spark SQL to accommodate structured and semi-structured data. The bedrock of Apache Spark is Spark Core, which is built on RDD abstraction.

Big Data 49

Big Data Project Metadata Programming Language 49

Knowledge Hut

JULY 24, 2023

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 Management NoSQL Relational Database 52

Knowledge Hut

APRIL 23, 2024

Data warehouses are typically built using traditional relational database systems, employing techniques like Extract, Transform, Load (ETL) to integrate and organize data. Data warehousing offers several advantages. By structuring data in a predefined schema, data warehouses ensure data consistency and accuracy.

Data Warehouse 52

Data Warehouse Big Data Unstructured Data Data Ingestion 52

Striim

SEPTEMBER 11, 2024

In an ETL-based architecture, data is first extracted from source systems, then transformed into a structured format, and finally loaded into data stores, typically data warehouses. This method is advantageous when dealing with structured data that requires pre-processing before storage.

Data Pipeline 98

Data Pipeline Designing Data Lake Data Warehouse 98

ProjectPro

JUNE 6, 2025

Wordsmith is a report-writing tool that can use structured data and LLMs to generate written summaries in plain language, perfect for business executives who prefer high-level insights. Real-Time Data Monitoring Agents These agents monitor data in real-time, providing immediate feedback or alerts based on the analysis.

Data Analysis 40

Data Analysis Building Raw Data Datasets 40

ProjectPro

JUNE 6, 2025

Identifying patterns is one of the key purposes of statistical data analysis. For instance, it can be helpful in the retail industry to find patterns in unstructured and semi-structured data to help make more effective decisions to improve the customer experience. Instead, they can simply import a library. and web services.

Data Analysis Tools 45

Data Analysis Tools Data Analysis BI R (Programming) 45

ProjectPro

JUNE 6, 2025

Relational Database Management Systems (RDBMS) Non-relational Database Management Systems Relational Databases primarily work with structured data using SQL (Structured Query Language). SQL works on data arranged in a predefined schema. Non-relational databases support dynamic schema for unstructured data.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

Knowledge Hut

DECEMBER 26, 2023

Analyzing more data points will therefore give you a more detailed insight into your study. The spectrum of sources from which data is collected for the study in Data Science is broad. It comes from numerous sources ranging from surveys, social media platforms, e-commerce websites, browsing searches, etc.

Data Engineering 98

Data Engineering Data Engineer Engineering Pipeline-centric 98

AltexSoft

JUNE 26, 2023

From the perspective of data science, all miscellaneous forms of data fall into three large groups: structured, semi-structured, and unstructured. Key differences between structured, semi-structured, and unstructured data. They can be accumulated in NoSQL databases like MongoDB or Cassandra.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

AltexSoft

NOVEMBER 10, 2021

The data in this case is checked against the pre-defined schema (internal database format) when being uploaded, which is known as the schema-on-write approach. Purpose-built, data warehouses allow for making complex queries on structured data via SQL (Structured Query Language) and getting results fast for business intelligence.

Architecture 52

Architecture Data Lake Data Warehouse Metadata 52

ProjectPro

AUGUST 6, 2015

Companies like Electronic Arts, Riot Games are using big data for keeping a track of game play which helps predict performance of the play by analysing 4TB of operational logs and 500GB of structured data. Sports brands like ESPN have also got on to the big data bandwagon.

Big Data 52

Big Data Insurance Hadoop Media 52

Edureka

AUGUST 27, 2024

It’s great for things like online shopping, IoT, gaming, social media, and real-time data analysis. Azure DB usually refers to SQL Database, which is for structured data, while Cosmos DB is for various types of data and is designed to work all over the world. Is Cosmos DB SQL or NoSQL?

NoSQL 40

NoSQL MongoDB SQL Database 40

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

Edureka

FEBRUARY 8, 2024

3D Rendering and Media Processing- High-performance computing is crucial for rendering graphics and processing media files. Instances like I3 and I4 offer a balance of compute power and storage performance, making them ideal for workloads that demand rapid and consistent access to large volumes of data.

AWS 52

AWS NoSQL Deep Learning Machine Learning 52

AltexSoft

JULY 27, 2021

TikTok – the China-based social media platform popular with teenagers – recommends accounts to follow with the help of user-centered modeling. The leading media streaming service says 80 percent of its watched content is based on algorithmic recommendations. How recommender systems work: data processing phases. Source: TikTok.

Machine Learning 76

Machine Learning Systems Algorithm Deep Learning 76

ProjectPro

OCTOBER 28, 2015

Hadoop Sqoop and Hadoop Flume are the two tools in Hadoop which is used to gather data from different sources and load them into HDFS. Sqoop in Hadoop is mostly used to extract structured data from databases like Teradata, Oracle, etc., The complexity of the big data system increases with each data source.

ETL Tools 52

ETL Tools Hadoop Relational Database Unstructured Data 52

ProjectPro

AUGUST 11, 2021

This means that a data warehouse is a collection of technologies and components that are used to store data for some strategic use. Data is collected and stored in data warehouses from multiple sources to provide insights into business data. Data from data warehouses is queried using SQL.

Data Lake 52

Data Lake Data Warehouse Cloud Hadoop 52

ProjectPro

NOVEMBER 14, 2015

Hadoop can be used to carry out data processing using either the traditional (map/reduce) or Spark-based (providing an interactive platform to process queries in real-time) approach. Hadoop came as a rescue when the data volume coming from different sources increased exponentially.

Hadoop 52

Hadoop Project Big Data Healthcare 52

AltexSoft

MARCH 14, 2023

It must collect, analyze, and leverage large amounts of customer data from various sources, including booking history from a CRM system, search queries tracked with Google Analytics, and social media interactions. Data sources component in a modern data stack. Data storage component in a modern data stack.

IT 59

IT Data Warehouse Data Governance Data Lake 59

ProjectPro

JUNE 6, 2015

“Solocal is a company that Yellow Media had always admired in terms of their ability to grow their online audiences.”-said We know that data warehouse is very big and a very complicated tool to maintain and to meet Big Data problems. In BI we just consider structured data.

Business Intelligence 40

Business Intelligence Big Data BI Hadoop 40

Edureka

JANUARY 18, 2024

Introduction of R as an optional language in data science, highlighting its strengths in statistics and visualization. Data Manipulation Examine the most important data manipulation libraries like explore Pandas for structured data manipulation and Numpy for numerical operations in Python.

Data Science 40

Data Science Deep Learning NoSQL Machine Learning 40

ProjectPro

APRIL 27, 2016

Apache Pig is a quick little porker like innovation on Hadoop that requires 1/16 th of the development time and 1/20 th lines of programming code in comparison to Hadoop MapReduce - with 43,000 servers in 20 YARN clusters and 600PB of data on HDFS to fulfil Yahoo’s search, personalization, media, advertising and communications efforts.

Hadoop 40

Hadoop Big Data Technology Kafka 40

Knowledge Hut

MARCH 27, 2024

MongoDB This free, open-source platform, which came into the limelight in 2010, is a document-oriented (NoSQL) database that is used to store a large amount of information in a structured manner. The first is the type of data you have, which will determine the tool you need.

Big Data 52

Big Data Data Analytics MongoDB Big Data Tools 52

Knowledge Hut

DECEMBER 26, 2023

Prepare and carry out all digital marketing strategies, including email, social media, SEO/SEM, and display advertising campaigns. Creating, establishing, and sustaining our social media presence. All digital marketing campaign performance is measured, reported, and evaluated against set objectives (ROI and KPIs).

Insurance 52

Insurance Banking Finance Recruitment 52

ProjectPro

NOVEMBER 15, 2021

With SQL, machine learning, real-time data streaming, graph processing, and other features, this leads to incredibly rapid big data processing. DataFrames are used by Spark SQL to accommodate structured and semi-structured data. The bedrock of Apache Spark is Spark Core, which is built on RDD abstraction.

Big Data 52

Big Data Project Metadata Programming Language 52

ProjectPro

JUNE 6, 2025

Hadoop vs RDBMS Criteria Hadoop RDBMS Datatypes Processes semi-structured and unstructured data. Processes structured data. Schema Schema on Read Schema on Write Best Fit for Applications Data discovery and Massive Storage/Processing of Unstructured data. are all examples of unstructured data.

Hadoop 40

Hadoop Big Data Metadata Java 40

ProjectPro

JULY 27, 2021

Relational Database Management Systems (RDBMS) Non-relational Database Management Systems Relational Databases primarily work with structured data using SQL (Structured Query Language). SQL works on data arranged in a predefined schema. Non-relational databases support dynamic schema for unstructured data.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

ProjectPro

AUGUST 21, 2015

Hadoop vs RDBMS Criteria Hadoop RDBMS Datatypes Processes semi-structured and unstructured data. Processes structured data. Schema Schema on Read Schema on Write Best Fit for Applications Data discovery and Massive Storage/Processing of Unstructured data. are all examples of unstructured data.

Hadoop 40

Hadoop Big Data Metadata Java 40

ProjectPro

JUNE 6, 2025

The project emphasizes security features and detailed data lineage tracking, ensuring robust data governance and compliance.​ Project Idea: Flask API Big Data Project using Databricks and Unity Catalog 12. It involves ingesting Twitter data, processing it, and visualizing trends and sentiments.

Project 64

Project Transportation Data Pipeline Datasets 64