ProjectPro

JANUARY 19, 2022

In 2017, Gartner predicted that 85%of the data-based projects would fail and deliver the desired results. Good knowledge of various machine learning and deep learning algorithms will be a bonus. Knowledge of popular big data tools like Apache Spark, Apache Hadoop, etc. Why do companies hire a Data Engineer?

Data Engineer 52

Data Engineer Data Engineering Engineering Amazon Web Services 52

ProjectPro

FEBRUARY 8, 2017

2017 will see a continuation of these big data trends as technology becomes smarter with the implementation of deep learning and AI by many organizations. Here’s a sneak-peak into what big data leaders and CIO’s predict on the emerging big data trends for 2017.

Big Data 40

Big Data Hadoop Data Lake Machine Learning 40

ProjectPro

MARCH 17, 2014

Big data and hadoop are catch-phrases these days in the tech media for describing the storage and processing of huge amounts of data. Over the years, big data has been defined in various ways and there is lots of confusion surrounding the terms big data and hadoop. Big Deal Companies are striking with Big Data Analytics What is Hadoop?

Hadoop 52

Hadoop Big Data Unstructured Data Retail 52

ProjectPro

JUNE 18, 2021

Instagram switched to Python as its primary programming language in 2017 and is using it ever since. However, frameworks like Apache Spark, Kafka, Hadoop, Hive, Cassandra, and Flink all run on the JVM (Java Virtual Machine) and are very important in the field of Big Data. It is built on Apache Hadoop MapReduce.

Java 52

Java Data Science Python Programming Language 52

ProjectPro

JANUARY 24, 2023

Ace your Big Data engineer interview by working on unique end-to-end solved Big Data Projects using Hadoop How to train a model using Amazon SageMaker? Once data is prepared, the next step is building machine learning models and training them. Amazon launched SageMaker in November 2017. FAQs When was SageMaker launched?

Building 52

Building Algorithm Machine Learning AWS 52

ProjectPro

DECEMBER 22, 2016

If you are aspiring to be a data analyst then the core competencies that you should be familiar with are distributed computing frameworks like Hadoop and Spark, knowledge of programming languages like Python, R , SAS, data munging, data visualization, math , statistics , and machine learning. How to create a sparse Matrix in Python?

Data Mining 52

Data Mining Data Cleanse Datasets Data Analysis 52

ProjectPro

JULY 23, 2021

AWS generated revenue of $18 Billion in 2017, and the figure has been aggressively rising since then. Ace your Big Data engineer interview by working on unique end-to-end solved Big Data Projects using Hadoop. With Amazon Polly, you can use advanced deep learning technologies to carry out accurate conversions.

AWS 52

AWS Project Amazon Web Services Cloud Computing 52

Knowledge Hut

DECEMBER 26, 2023

Most of the Data engineers working in the field enroll themselves in several other training programs to learn an outside skill, such as Hadoop or Big Data querying, alongside their Master's degree and PhDs. What is the difference between Supervised and Unsupervised Learning?

Data Engineer 98

Data Engineer Data Engineering Engineering Pipeline-centric 98

ProjectPro

APRIL 1, 2017

News on Hadoop-March 2017 The cloud is disrupting Hadoop. Zdnet.com, March 6, 2017 Forrester estimates that organizations will spend $800 million in hadoop and its related services in 2017. Just like Hadoop is not designed for the cloud, it is not meant for doing matrix math that deep learning requires.

Hadoop 40

Hadoop Data Lake Electronics Big Data 40