Towards Data Science
JANUARY 16, 2024
Image by the author 2004 to 2010 — The elephant enters the room New wave of applications emerged — Social Media, Software observability, etc. Result: Hadoop & NoSQL frameworks emerged. New data formats emerged — JSON, Avro, Parquet, XML etc. Data lakes were introduced to store the new data formats.
Knowledge Hut
APRIL 26, 2024
In the age of big data processing, how to store these terabytes of data surfed over the internet was the key concern of companies until 2010. Another main aspect of this position is database design (RDBMS, NoSQL, and NewSQL), data warehousing, and setting up a data lake.
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Knowledge Hut
DECEMBER 25, 2023
Databases are divided into two categories, which are NoSQL(MongoDB) and SQL(PostgreSQL, MySQL, Oracle) databases. It all started with the release of AngularJS in 2010. So, we need to choose one backend framework from Java (Spring Framework), JavaScript (NodeJS), etc, and then also learn databases.
Rockset
JANUARY 23, 2019
In this query, I am tokenizing the title , extracting the year from the the time field, and returning the number of occurrences of "data" in the tokens, grouped by year. Let's first check how user engagement around blockchain and cryptocurrencies has been trending.
ProjectPro
APRIL 17, 2015
This articles explores four latest trends in big data analytics that are driving implementation of cutting edge technologies like Hadoop and NoSQL. billion in 2010 to $17 billion in 2015 with estimates that the Big Data Analytics services market is growing 6 times faster than the entire IT sector. during 2014 - 2020.
ProjectPro
JANUARY 19, 2022
AWS has the top-most share in the market, and that’s primarily because it was launched in 2002 while Microsoft and Google launched their cloud computing services in 2010 and 2009, respectively. Depending on the company you want to work with, you will be asked to learn them deeply.
ProjectPro
JUNE 29, 2016
As open source technologies gain popularity at a rapid pace, professionals who can upgrade their skillset by learning fresh technologies like Hadoop, Spark, NoSQL, etc. Learning big data technologies will help Singaporeans fulfil the demand vs. supply shortage for analytics skills like Hadoop, Spark, Machine Learning, Cassandra, NoSQL, etc.
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