ProjectPro

NOVEMBER 14, 2015

Big data has taken over many aspects of our lives and as it continues to grow and expand, big data is creating the need for better and faster data storage and analysis. These Apache Hadoop projects are mostly into migration, integration, scalability, data analytics, and streaming analysis. Data Migration 2.

Hadoop 52

Hadoop Project Big Data Healthcare 52

Knowledge Hut

DECEMBER 26, 2023

Businesses benefit at large with these data collection and analysis as they allow organizations to make predictions and give insights about products so that they can make informed decisions, backed by inferences from existing data, which, in turn, helps in huge profit returns to such businesses. What is the role of a Data Engineer?

Data Engineering 98

Data Engineering Data Engineer Engineering Hadoop 98

Knowledge Hut

DECEMBER 22, 2023

They can categorize and cluster raw data using algorithms, spot hidden patterns and connections in it, and continually learn and improve over time. Hadoop Gigabytes to petabytes of data may be stored and processed effectively using the open-source framework known as Apache Hadoop.

Hadoop 98

Hadoop Deep Learning Data Science Machine Learning 98

ProjectPro

JULY 3, 2015

SAP is all set to ensure that big data market knows its hip to the trend with its new announcement at a conference in San Francisco that it will embrace Hadoop. What follows is an elaborate explanation on how SAP and Hadoop together can bring in novel big data solutions to the enterprise.

Hadoop 40

Hadoop Big Data Data Solutions Unstructured Data 40

ProjectPro

MARCH 23, 2015

was intensive and played a significant role in processing large data sets, however it was not an ideal choice for interactive analysis and was constrained for machine learning, graph and memory intensive data analysis algorithms. In one of our previous articles we had discussed about Hadoop 2.0

Hadoop 40

Hadoop Big Data Architecture Kafka 40

The Pragmatic Engineer

JUNE 13, 2023

The company’s largest data cluster is 20-30PB (petabytes: 1PB is 1,000 terabytes or 1M gigabytes). Ten years ago, this data cluster was 300GB as a Hadoop cluster; that’s around a 100,000-fold increase in data stored! The company runs 4 data centers: in the US and Europe, with two in Asia.

Cloud 242

Cloud Database Utilities BI 242

ProjectPro

APRIL 27, 2016

Scott Gnau, CTO of Hadoop distribution vendor Hortonworks said - "It doesn't matter who you are — cluster operator, security administrator, data analyst — everyone wants Hadoop and related big data technologies to be straightforward. Curious to know about these Hadoop innovations?

Hadoop 40

Hadoop Big Data Technology Kafka 40

Christophe Blefari

JUNE 21, 2024

One way to read data platforms When we look at platforms history what characterises evolution is the separation (or not) between the engine and the storage. This enables easier data management and query operations, making it possible to perform SQL-like operations and transactions directly on data files.

Metadata 147

Metadata Data Warehouse BI MySQL 147

Precisely

MARCH 9, 2023

As cloud computing platforms make it possible to perform advanced analytics on ever larger and more diverse data sets, new and innovative approaches have emerged for storing, preprocessing, and analyzing information. Hadoop, Snowflake, Databricks and other products have rapidly gained adoption. They can be changed, but not easily.

Data Lake 58

Data Lake Data Warehouse Hadoop Raw Data 58

Data Engineering Podcast

DECEMBER 16, 2019

You work hard to make sure that your data is clean, reliable, and reproducible throughout the ingestion pipeline, but what happens when it gets to the data warehouse? Dataform picks up where your ETL jobs leave off, turning raw data into reliable analytics.

Metadata 100

Metadata PostgreSQL Datasets Data Warehouse 100

Confluent

SEPTEMBER 26, 2019

In the early days, many companies simply used Apache Kafka ® for data ingestion into Hadoop or another data lake. ® , Go, and Python SDKs where an application can use SQL to query raw data coming from Kafka through an API (but that is a topic for another blog). However, Apache Kafka is more than just messaging.

Kafka 21

Kafka SQL BI Hadoop 21

ProjectPro

AUGUST 21, 2015

With the help of ProjectPro’s Hadoop Instructors, we have put together a detailed list of big data Hadoop interview questions based on the different components of the Hadoop Ecosystem such as MapReduce, Hive, HBase, Pig, YARN, Flume, Sqoop , HDFS, etc. What is the difference between Hadoop and Traditional RDBMS?

Hadoop 40

Hadoop Big Data Metadata Java 40

ProjectPro

MARCH 14, 2014

Every department of an organization including marketing, finance and HR are now getting direct access to their own data. This is creating a huge job opportunity and there is an urgent requirement for the professionals to master Big Data Hadoop skills. In 2015, big data has evolved beyond the hype.

Hadoop 40

Hadoop Big Data Data Mining Retail 40

U-Next

MARCH 7, 2023

Taking data from sources and storing or processing it is known as data extraction. Define Data Wrangling The process of data wrangling involves cleaning, structuring, and enriching raw data to make it more useful for decision-making. Data is discovered, structured, cleaned, enriched, validated, and analyzed.

Data Mining 96

Data Mining Government Scala Data Governance 96

AltexSoft

MAY 14, 2021

Modern technologies allow gathering both structured (data that comes in tabular formats mostly) and unstructured data (all sorts of data formats) from an array of sources including websites, mobile applications, databases, flat files, customer relationship management systems (CRMs), IoT sensors, and so on. Apache Hadoop.

Big Data 78

Big Data Data Analytics IT NoSQL 78

Monte Carlo

MAY 28, 2024

Batch Processing Tools For batch processing, tools like Apache Hadoop and Spark are widely used. Hadoop handles large-scale data storage and processing, while Spark offers fast in-memory computing capabilities for further processing.

Data Ingestion 52

Data Ingestion Architecture Designing Hadoop 52

Cloud Academy

JANUARY 27, 2022

A data engineer is an engineer who creates solutions from raw data. A data engineer develops, constructs, tests, and maintains data architectures. Let’s review some of the big picture concepts as well finer details about being a data engineer. Earlier we mentioned ETL or extract, transform, load.

Certification 52

Certification Data Engineering Data Engineer Engineering 52

LinkedIn Engineering

APRIL 4, 2023

System Architecture Overview Setup We wanted to build a single data processing pipeline that would be efficient and scalable as more metrics are added. The data needed to compute our metrics came from various sources including MySQL databases, Kafka topics and Hadoop (HDFS). from the metric’s processing logic (i.e.

MySQL 122

MySQL Datasets Software Engineer Software Engineering 122

Knowledge Hut

AUGUST 16, 2024

Having a sound knowledge of either of these programming languages is enough to have a successful career in Data Science. Excel Excel is another very important prerequisite for Data Science. It is an important tool to understand, manipulate, analyze and visualize data. In such a scenario, Hadoop comes to the rescue.

Data Science 52

Data Science Hadoop Unstructured Data Programming Language 52

ProjectPro

JANUARY 31, 2023

Big data operations require specialized tools and techniques since a relational database cannot manage such a large amount of data. Big data enables businesses to gain a deeper understanding of their industry and helps them extract valuable information from the unstructured and raw data that is regularly collected.

Big Data 52

Big Data Hadoop Relational Database AWS 52

AltexSoft

MARCH 14, 2023

Data storage The tools mentioned in the previous section are instrumental in moving data to a centralized location for storage, usually, a cloud data warehouse, although data lakes are also a popular option. But this distinction has been blurred with the era of cloud data warehouses.

IT 59

IT Data Warehouse Data Governance Data Lake 59

Knowledge Hut

JANUARY 12, 2024

Data Engineer Data Engineers' responsibility is to process raw data and extract useful information, such as market insights and trend details, from the data. Education requirements: Bachelor's degrees in computer science or a related field are common among data engineers.

Cloud Computing 98

Cloud Computing Cloud Computer Science Education 98

U-Next

SEPTEMBER 7, 2022

Autonomous data warehouse from Oracle. . What is Data Lake? . Essentially, a data lake is a repository of raw data from disparate sources. A data lake stores current and historical data similar to a data warehouse. Data Lake Vs. Data Warehouse: Latest Industry Stats .

Data Lake 52

Data Lake Data Warehouse Unstructured Data Amazon Web Services 52

AltexSoft

MAY 12, 2023

Without a fixed schema, the data can vary in structure and organization. File systems, data lakes, and Big Data processing frameworks like Hadoop and Spark are often utilized for managing and analyzing unstructured data. There are several widely used unstructured data storage solutions such as data lakes (e.g.,

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

ProjectPro

FEBRUARY 16, 2023

According to the 8,786 data professionals participating in Stack Overflow's survey, SQL is the most commonly-used language in data science. Despite the buzz surrounding NoSQL , Hadoop , and other big data technologies, SQL remains the most dominant language for data operations among all tech companies.

Data Engineer 52

Data Engineer Data Engineering SQL Engineering 52

Edureka

JULY 4, 2024

It is a cloud-based service by Amazon Web Services (AWS) that simplifies processing large, distributed datasets using popular open-source frameworks, including Apache Hadoop and Spark. Arranging the raw data could composite a 360-degree view of your sales customer integration across all channels. Is AWS EMR open-source?

AWS 52

AWS Amazon Web Services Hadoop Big Data 52

ProjectPro

JANUARY 19, 2022

The first step is to work on cleaning it and eliminating the unwanted information in the dataset so that data analysts and data scientists can use it for analysis. That needs to be done because raw data is painful to read and work with. Knowledge of popular big data tools like Apache Spark, Apache Hadoop, etc.

Data Engineering 52

Data Engineering Data Engineer Engineering Amazon Web Services 52

ProjectPro

SEPTEMBER 26, 2021

As a Big Data Engineer, you shall also know and understand the Big Data architecture and Big Data tools. Hadoop , Kafka , and Spark are the most popular big data tools used in the industry today. You will get to learn about data storage and management with lessons on Big Data tools.

Big Data 52

Big Data Data Engineering Data Engineer Engineering 52

Knowledge Hut

SEPTEMBER 6, 2023

It will help you master the skill of deriving insights from raw data and use cutting edge tools to develop models which can help in making viable business decisions. Data Science Bootcamp course from KnowledgeHut will help you gain knowledge on different data engineering concepts.

Data Science 97

Data Science Certification Business Analyst Machine Learning 97

Monte Carlo

APRIL 24, 2023

By accommodating various data types, reducing preprocessing overhead, and offering scalability, data lakes have become an essential component of modern data platforms , particularly those serving streaming or machine learning use cases. Not to mention seamless integration with the Oracle ecosystem.

Data Lake 52

Data Lake Google Cloud Data Warehouse AWS 52

Knowledge Hut

APRIL 23, 2024

Data Science is the field that focuses on gathering data from multiple sources using different tools and techniques. Whereas, Business Intelligence is the set of technologies and applications that are helpful in drawing meaningful information from raw data.

Business Intelligence 52

Business Intelligence Data Science BI Unstructured Data 52

Monte Carlo

AUGUST 25, 2023

While data lake vendors are constantly emerging to provide more managed services — like Databricks’ Delta Lake, Dremio, and even Snowflake — traditionally, data lakes have been created by combining various technologies. Storage can utilize S3, Google Cloud Storage, Microsoft Azure Blob Storage, or Hadoop HDFS.

Data Lake 52

Data Lake Data Warehouse Unstructured Data Raw Data 52

Edureka

AUGUST 29, 2024

In this respect, the purpose of the blog is to explain what is a data engineer , describe their duties to know the context that uses data, and explain why the role of a data engineer is central. What Does a Data Engineer Do? Design algorithms transforming raw data into actionable information for strategic decisions.

Data Engineering 40

Data Engineering Data Engineer Engineering Generalist 40

Knowledge Hut

JANUARY 18, 2024

The role can also be defined as someone who has the knowledge and skills to generate findings and insights from available raw data. Data Engineer A professional who has expertise in data engineering and programming to collect and covert raw data and build systems that can be usable by the business.

Data Science 98

Data Science Deep Learning Business Analyst Data Mining 98

Knowledge Hut

DECEMBER 29, 2023

A Data Engineer is someone proficient in a variety of programming languages and frameworks, such as Python, SQL, Scala, Hadoop, Spark, etc. One of the primary focuses of a Data Engineer's work is on the Hadoop data lakes. NoSQL databases are often implemented as a component of data pipelines.

Data Science 98

Data Science Data Mining Deep Learning Programming Language 98

ProjectPro

JUNE 9, 2021

Data Science- Definition Data Science is an interdisciplinary branch encompassing data engineering and many other fields. Data Science involves applying statistical techniques to raw data, just like data analysts, with the additional goal of building business solutions. Machine learning skills.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Science 52

Rockset

AUGUST 25, 2021

They are an essential part of the modern data stack for powering: Real-time search applications Social features in the product Recommendation/rewards features in the product Real-time dashboards IoT applications These use cases can have several TBs per day streaming in - they are literally data torrents.

Aggregated Data 52

Aggregated Data Hadoop SQL Data Lake 52