Towards Data Science

MARCH 5, 2024

Introduction In the field of data warehousing, there’s a universal truth: managing data can be costly. Like a dragon guarding its treasure, each byte stored and each query executed demands its share of gold coins. But let me give you a magical spell to appease the dragon: burn data, not money!

Bytes 71

Bytes Google Cloud Cloud Storage Utilities 71

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 AWS Relational Database 52

Edureka

FEBRUARY 7, 2023

One can use polybase: From Azure SQL Database or Azure Synapse Analytics, query data kept in Hadoop, Azure Blob Storage, or Azure Data Lake Store. It does away with the requirement to import data from an outside source. Export information to Azure Data Lake Store, Azure Blob Storage, or Hadoop.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Lake 52

ProjectPro

NOVEMBER 22, 2021

MapReduce Apache Spark Only batch-wise data processing is done using MapReduce. Apache Spark can handle data in both real-time and batch mode. The data is stored in HDFS (Hadoop Distributed File System), which takes a long time to retrieve. You can learn a lot by utilizing PySpark for data intake processes.

Hadoop 52

Hadoop Python Datasets Metadata 52