Rockset

FEBRUARY 2, 2022

Developers choose this database because of its flexible data model and its inherent scalability as a NoSQL database. Yet, analytics is now a vital part of modern data applications. The benefit of these tools is that they’re built specifically for data analytics. The downsides of data warehouses are data and query latency.

MongoDB 52

MongoDB NoSQL Data Warehouse BI 52

Ascend.io

SEPTEMBER 14, 2023

Use Case: Transforming monthly sales data to weekly averages import dask.dataframe as dd data = dd.read_csv('large_dataset.csv') mean_values = data.groupby('category').mean().compute() compute() Data Storage Python extends its mastery to data storage, boasting smooth integrations with both SQL and NoSQL databases.

Data Engineering 52

Data Engineering Data Engineer Python Engineering 52

ProjectPro

APRIL 20, 2017

There are various kinds of hadoop projects that professionals can choose to work on which can be around data collection and aggregation, data processing, data transformation or visualization. How small file problems in streaming can be resolved using a NoSQL database. Followed by MySQL is the Microsoft SQL Server.

Hadoop 40

Hadoop Big Data Coding Project 40

Knowledge Hut

SEPTEMBER 6, 2023

Over the past decade, the IT world transformed with a data revolution. The rise of big data and NoSQL changed the game. Systems evolved from simple to complex, and we had to split how we find data from where we store it. Skills acquired : Relational database concepts Retrieving data using the SQL SELECT statement.

Database 52

Database Certification MongoDB MySQL 52

DareData

JANUARY 30, 2023

For data scientists, these skills are extremely helpful when it comes to manage and build more optimized data transformation processes, helping models achieve better speed and relability when set in production. Examples of relational databases include MySQL or Microsoft SQL Server.

Data Engineering 52

Data Engineering Data Engineer NoSQL Engineering 52

ProjectPro

OCTOBER 28, 2015

Apache Sqoop (SQL-to-Hadoop) is a lifesaver for anyone who is experiencing difficulties in moving data from the data warehouse into the Hadoop environment. Apache Sqoop is an effective hadoop tool used for importing data from RDBMS’s like MySQL, Oracle, etc. into HBase, Hive or HDFS.

ETL Tools 52

ETL Tools Hadoop Relational Database Unstructured Data 52

AltexSoft

OCTOBER 21, 2022

This enables systems using Kafka to aggregate data from many sources and to make it consistent. Instead of interfering with each other, Kafka consumers create groups and split data among themselves. cloud data warehouses — for example, Snowflake , Google BigQuery, and Amazon Redshift.

Kafka 93

Kafka Hadoop ETL Tools Big Data 93