Cloudera

JUNE 25, 2021

Using easy-to-define policies, Replication Manager solves one of the biggest barriers for the customers in their cloud adoption journey by allowing them to move both tables/structured data and files/unstructured data to the CDP cloud of their choice easily. Specification of access conditions for specific users and groups.

Cloud 69

Cloud Data Lake Cloud Storage Metadata 69

Knowledge Hut

SEPTEMBER 29, 2023

The Azure Data Engineer Certification test evaluates one's capacity for organizing and putting into practice data processing, security, and storage, as well as their capacity for keeping track of and maximizing data processing and storage. They control and safeguard the flow of organized and unstructured data from many sources.

Certification 52

Certification Data Engineering Data Engineer Engineering 52

Cloudera

SEPTEMBER 1, 2020

DDE also makes it much easier for application developers or data workers to self-service and get started with building insight applications or exploration services based on text or other unstructured data (i.e. data best served through Apache Solr). Coordinates distribution of data and metadata, also known as shards.

Cloud Storage 67

Cloud Storage Unstructured Data AWS Analytics Application 67

Monte Carlo

MAY 14, 2024

Depending on the quantity of data flowing through an organization’s pipeline — or the format the data typically takes — the right modern table format can help to make workflows more efficient, increase access, extend functionality, and even offer new opportunities to activate your unstructured data.

Data Lake 52

Data Lake Metadata Hadoop Data Governance 52

Cloudera

AUGUST 30, 2018

Consider the following practices that, until recently, were relegated to the R&D department: Data-driven decision making – the collection and analysis of data to guide decisions that improve success.

Unstructured Data 40

Unstructured Data Machine Learning Data Warehouse BI 40

AltexSoft

JULY 29, 2022

Depending on how you measure it, the answer will be 11 million newspaper pages or… just one Hadoop cluster and one tech specialist who can move 4 terabytes of textual data to a new location in 24 hours. The Hadoop toy. So the first secret to Hadoop’s success seems clear — it’s cute. What is Hadoop?

Hadoop 59

Hadoop Big Data Google Cloud NoSQL 59

AltexSoft

JUNE 7, 2021

Hadoop and Spark are the two most popular platforms for Big Data processing. They both enable you to deal with huge collections of data no matter its format — from Excel tables to user feedback on websites to images and video files. What are its limitations and how do the Hadoop ecosystem address them? What is Hadoop.

Big Data Tools 98

Big Data Tools Hadoop Big Data Database-centric 98

Monte Carlo

AUGUST 25, 2023

One advantage of data warehouses is their integrated nature. As fully managed solutions, data warehouses are designed to offer ease of construction and operation. A warehouse can be a one-stop solution, where metadata, storage, and compute components come from the same place and are under the orchestration of a single vendor.

Data Lake 52

Data Lake Data Warehouse Unstructured Data Raw Data 52

ProjectPro

OCTOBER 28, 2015

Apache Hadoop is synonymous with big data for its cost-effectiveness and its attribute of scalability for processing petabytes of data. Data analysis using hadoop is just half the battle won. Getting data into the Hadoop cluster plays a critical role in any big data deployment.

ETL Tools 52

ETL Tools Hadoop Relational Database Unstructured Data 52

Cloudera

SEPTEMBER 15, 2022

It was designed as a native object store to provide extreme scale, performance, and reliability to handle multiple analytics workloads using either S3 API or the traditional Hadoop API. Structured data (such as name, date, ID, and so on) will be stored in regular SQL databases like Hive or Impala databases.

Systems 86

Systems Hadoop Metadata Telecommunication 86

ProjectPro

JANUARY 31, 2023

Big data enables businesses to get valuable insights into their products or services. Almost every company employs data models and big data technologies to improve its techniques and marketing campaigns. Most leading companies use big data analytical tools to enhance business decisions and increase revenues.

Big Data 52

Big Data Hadoop AWS Relational Database 52

ProjectPro

AUGUST 11, 2021

Is Snowflake a data lake or data warehouse? Is Hadoop a data lake or data warehouse? The data warehouse layer consists of the relational database management system (RDBMS) that contains the cleaned data and the metadata, which is data about the data.

Data Lake 52

Data Lake Data Warehouse Cloud Hadoop 52

ProjectPro

FEBRUARY 18, 2016

Apache Hadoop, an open source framework is used widely for processing gigantic amounts of unstructured data on commodity hardware. Four core modules form the Hadoop Ecosystem : Hadoop Common, HDFS, YARN and MapReduce. Apache Zookeeper and Oozie are the Hadoop admin tools used for this purpose.

Hadoop 40

Hadoop Management Metadata Java 40

ProjectPro

SEPTEMBER 16, 2021

NoSQL databases are the new-age solutions to distributed unstructured data storage and processing. The speed, scalability, and fail-over safety offered by NoSQL databases are needed in the current times in the wake of Big Data Analytics and Data Science technologies. Hence, writes in Hbase are operation intensive.

NoSQL 52

NoSQL Database Hadoop Big Data 52

ProjectPro

SEPTEMBER 26, 2021

Becoming a Big Data Engineer - The Next Steps Big Data Engineer - The Market Demand An organization’s data science capabilities require data warehousing and mining, modeling, data infrastructure, and metadata management. Most of these are performed by Data Engineers.

Big Data 52

Big Data Data Engineering Data Engineer Engineering 52

ProjectPro

AUGUST 11, 2016

When people talk about big data analytics and Hadoop, they think about using technologies like Pig, Hive , and Impala as the core tools for data analysis. R and Hadoop combined together prove to be an incomparable data crunching tool for some serious big data analytics for business.

Hadoop 40

Hadoop Big Data R (Programming) Programming Language 40

AltexSoft

JUNE 26, 2023

Commonly, the entire flow is fully automated and consists of three main steps — data extraction, transformation, and loading ( ETL or ELT , for short, depending on the order of the operations.) Dive deeper into the subject by reading our article Data Integration: Approaches, Techniques, Tools, and Best Practices for Implementation.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

ProjectPro

APRIL 11, 2016

Let’s face it; the Hadoop Interview process is a tough cookie to crumble. If you are planning to pursue a job in the big data domain as a Hadoop developer , you should be prepared for both open-ended interview questions and unique technical hadoop interview questions asked by the hiring managers at top tech firms.

Hadoop 40

Hadoop Big Data Java Unstructured Data 40

Monte Carlo

JUNE 14, 2023

This frequently involves, in some order, extraction (from a source system), transformation (where data is combined with other data and put into the desired format), and loading (into storage where it can be accessed). Most organizations deploy some or all of these data pipeline architectures.

Data Pipeline 52

Data Pipeline Architecture Data Lake Data Warehouse 52

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

Cloudera

AUGUST 21, 2020

Perhaps one of the most significant contributions in data technology advancement has been the advent of “Big Data” platforms. Historically these highly specialized platforms were deployed on-prem in private data centers to ensure greater control , security, and compliance. But the “elephant in the room” is NOT ‘Hadoop’.

Hadoop 73

Hadoop Big Data Cloud Kafka 73

ProjectPro

JANUARY 27, 2016

Installing Hadoop cluster in production is just half the battle won. It is extremely important for a Hadoop admin to tune the Hadoop cluster setup to gain maximum performance. During Hadoop installation , the cluster is configured with default configuration settings which are on par with the minimal hardware configuration.

Hadoop 40

Hadoop Big Data Unstructured Data Portfolio 40

AltexSoft

DECEMBER 23, 2022

Organizations now operate huge amounts of various data stored in multiple systems. ELT makes it easier to manage and access all this information by allowing both raw and cleaned data to be loaded and stored for further analysis. In this case, ELT can help you improve performance and make data available immediately.

Process 52

Process Building Raw Data Data Lake 52

ProjectPro

APRIL 4, 2015

With the help of our best in class Hadoop faculty, we have gathered top Hadoop developer interview questions that will help you get through your next Hadoop job interview. IT organizations from various domains are investing in big data technologies, increasing the demand for technically competent Hadoop developers.

Hadoop 40

Hadoop Big Data Recruitment Java 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 Metadata 40

AltexSoft

NOVEMBER 10, 2021

At the same time, it brings structure to data and empowers data management features similar to those in data warehouses by implementing the metadata layer on top of the store. Traditional data warehouse platform architecture. Key features of a data lakehouse. Unstructured and streaming data support.

Architecture 52

Architecture Data Lake Data Warehouse Metadata 52

AltexSoft

NOVEMBER 23, 2021

Not to mention that additional sources are constantly being added through new initiatives like big data analytics , cloud-first, and legacy app modernization. To break data silos and speed up access to all enterprise information, organizations can opt for an advanced data integration technique known as data virtualization.

Process 69

Process Data Lake Metadata Data Warehouse 69

ProjectPro

FEBRUARY 8, 2017

Here’s a sneak-peak into what big data leaders and CIO’s predict on the emerging big data trends for 2017. The need for speed to use Hadoop for sentiment analysis and machine learning has fuelled the growth of hadoop based data stores like Kudu and adoption of faster databases like MemSQL and Exasol.

Big Data 40

Big Data Hadoop Data Lake Data Governance 40

ProjectPro

NOVEMBER 30, 2021

In extract-transform-load (ETL), data is obtained from multiple sources, transformed, and stored in a single data warehouse, with access to data analysts , data scientists , and business analysts for data visualization and statistical analysis model building, forecasting, etc.

Process 52

Process Data Pipeline Data Warehouse AWS 52

AltexSoft

MAY 12, 2023

In today’s data-driven world, organizations amass vast amounts of information that can unlock significant insights and inform decision-making. A staggering 80 percent of this digital treasure trove is unstructured data, which lacks a pre-defined format or organization. What is unstructured data?

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

AltexSoft

SEPTEMBER 21, 2023

These indices are specially designed data structures that map out the data for rapid searches, allowing for the retrieval of queries in milliseconds. As a result, Elasticsearch is exceptionally efficient in managing structured and unstructured data. Framework Programming The Good and the Bad of Node.js

Engineering 52

Engineering NoSQL Programming Language Java 52

ProjectPro

AUGUST 24, 2021

Thus, as a learner, your goal should be to work on projects that help you explore structured and unstructured data in different formats. Data Warehousing: Data warehousing utilizes and builds a warehouse for storing data. A data engineer interacts with this warehouse almost on an everyday basis.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

ProjectPro

AUGUST 24, 2016

In spite of a few rough edges, HBase has become a shining sensation within the white hot Hadoop market. However, Hadoop cannot handle high velocity of random writes and reads and also cannot change a file without completely rewriting it. If you need random access, you have to have HBase."- said Gartner analyst Merv Adrian.

Architecture 40

Architecture IT Hadoop NoSQL 40

ProjectPro

JULY 30, 2021

Map-reduce - Map-reduce enables users to use resizable Hadoop clusters within Amazon infrastructure. Amazon’s counterpart of this is called Amazon EMR ( Elastic Map-Reduce) Hadoop - Hadoop allows clustering of hardware to analyse large sets of data in parallel. What are the basic types of Data Centers?

Cloud Computing 40

Cloud Computing Cloud Amazon Web Services AWS 40

ProjectPro

DECEMBER 10, 2021

Azure Cloud Services are hosted on virtual machines, and they let one have a higher degree of control over the VMs by allowing software installation on the VMs and also making them remotely accessible. A user only pays for the resources he needs from a cloud service provider and accesses them over a secure Internet connection.

BI 52

BI Cloud Computing SQL Database 52

AltexSoft

MARCH 30, 2023

Source: Databricks Delta Lake is an open-source, file-based storage layer that adds reliability and functionality to existing data lakes built on Amazon S3, Google Cloud Storage, Azure Data Lake Storage, Alibaba Cloud, HDFS ( Hadoop distributed file system), and others. Delta Lake integrations.

Scala 64

Scala Data Lake BI Google Cloud 64

Cloudera

NOVEMBER 22, 2021

Open source frameworks such as Apache Impala, Apache Hive and Apache Spark offer a highly scalable programming model that is capable of processing massive volumes of structured and unstructured data by means of parallel execution on a large number of commodity computing nodes. . benchmarking study conducted by independent 3rd party ).

Government 89

Government Hadoop Data Security Data Warehouse 89