ProjectPro

JUNE 6, 2015

At ProjectPro we had the pleasure to invite Abed Ajraou , the Director of the BI & Big Data in Solocal Group (Yellow Pages in France) to speak about the digital transformation from BI to Big Data. BI is not a tool, a report or a database. The goal of BI is to create intelligence through Data. So what is BI?

Business Intelligence 40

Business Intelligence Big Data BI Hadoop 40

Knowledge Hut

SEPTEMBER 26, 2023

Supports Structured and Unstructured Data: One of Azure Synapse's standout features is its versatility in handling a wide array of data types. Whether your data is structured, like traditional relational databases, or unstructured, such as textual data, images, or log files, Azure Synapse can manage it effectively.

Data Lake 52

Data Lake Database-centric Machine Learning Pipeline-centric 52

Knowledge Hut

OCTOBER 30, 2023

Data Transformation and ETL: Handle more complex data transformation and ETL (Extract, Transform, Load) processes, including handling data from multiple sources and dealing with complex data structures. Ensure compliance with data protection regulations. Define data architecture standards and best practices.

BI 52

BI Business Intelligence Data Cleanse Business Analyst 52

Rockset

AUGUST 2, 2023

This enrichment data has changing schemas and new data providers are constantly being added to enhance the insights, making it challenging for Windward to support using relational databases with strict schemas. Windward also used specialized databases like Elasticsearch for specific functionality like text search.

Database-centric 52

Database-centric PostgreSQL Transportation Insurance 52

ProjectPro

JANUARY 31, 2023

Big Data is a collection of large and complex semi-structured and unstructured data sets that have the potential to deliver actionable insights using traditional data management tools. Big data operations require specialized tools and techniques since a relational database cannot manage such a large amount of data.

Big Data 52

Big Data Hadoop Relational Database AWS 52

AltexSoft

NOVEMBER 10, 2021

The pun being obvious, there’s more to that than just a new term: Data lakehouses combine the best features of both data lakes and data warehouses and this post will explain this all. What is a data lakehouse? Data warehouse. Traditional data warehouse platform architecture. websites, etc.

Architecture 52

Architecture Data Lake Data Warehouse Metadata 52

AltexSoft

AUGUST 29, 2023

Also, data lakes support ELT (Extract, Load, Transform) processes, in which transformation can happen after the data is loaded in a centralized store. A data lakehouse may be an option if you want the best of both worlds. Data sources can be broadly classified into three categories. Structured data sources.

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

AltexSoft

JULY 19, 2022

In the last few decades, we’ve seen a lot of architectural approaches to building data pipelines , changing one another and promising better and easier ways of deriving insights from information. There have been relational databases, data warehouses, data lakes, and even a combination of the latter two.

Architecture 52

Architecture Data Lake Medical Datasets 52

Knowledge Hut

DECEMBER 26, 2023

The job of a data engineer is to develop models using machine learning to scan, label and organize this unstructured data. This process helps convert the unstructured data into structured data, which can easily be collected and interpreted using analytical tools.

Data Engineering 98

Data Engineering Data Engineer Engineering Hadoop 98

ProjectPro

JANUARY 19, 2022

Data engineering is a new and ever-evolving field that can withstand the test of time and computing developments. Companies frequently hire certified Azure Data Engineers to convert unstructured data into useful, structured data that data analysts and data scientists can use.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Storage 52

ProjectPro

FEBRUARY 16, 2023

Data engineers are responsible for these data integration and ELT tasks, where the initial step requires extracting data from different types of databases/files, such as RDBMS, flat files, etc. Engineers can also use the "LOAD DATA INFILE" command to extract data from flat files like CSV or TXT.

Data Engineering 52

Data Engineering Data Engineer SQL Engineering 52

ProjectPro

NOVEMBER 14, 2015

Data Migration RDBMSs were inefficient and failed to manage the growing demand for current data. This failure of relational database management systems triggered organizations to move their data from RDBMS to Hadoop. This data can be analysed using big data analytics to maximise revenue and profits.

Hadoop 52

Hadoop Project Big Data Healthcare 52

ProjectPro

JULY 27, 2021

Differentiate between relational and non-relational database management systems. Relational Database Management Systems (RDBMS) Non-relational Database Management Systems Relational Databases primarily work with structured data using SQL (Structured Query Language).

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

ProjectPro

DECEMBER 7, 2021

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. What is a Big Data Pipeline?

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 52

ProjectPro

MAY 31, 2021

The project develops a data processing chain in a big data environment using Amazon Web Services (AWS) cloud tools, including steps like dimensionality reduction and data preprocessing and implements a fruit image classification engine. Machines and humans are both sources of structured data.

Big Data 52

Big Data Coding Project Hadoop 52