AltexSoft

FEBRUARY 11, 2023

They also define KPIs to measure and track the performance of the entire data infrastructure and its separate components. If KPI goals are not met, a data architect recommends solutions (including new technologies) to improve the existing framework. However, the relevant educational background is not the only requirement.

Data Architect 87

Data Architect Certification Generalist Big Data 87

Knowledge Hut

DECEMBER 29, 2023

The market for analytics is flourishing, as is the usage of the phrase Data Science. Professionals from a variety of disciplines use data in their day-to-day operations and feel the need to understand cutting-edge technology to get maximum insights from the data, therefore contributing to the growth of the organization.

Data Science 98

Data Science Data Mining Deep Learning Programming Language 98

Knowledge Hut

APRIL 3, 2023

The field of Backend Development is constantly evolving, and staying up-to-date with the latest tools and technologies is crucial for success. These include: A strong foundation in computer science, including knowledge of algorithms, data structures, and programming languages. Experience working with databases and APIs.

Programming Language 52

Programming Language Computer Science Portfolio PostgreSQL 52

ProjectPro

APRIL 1, 2016

NetworkAsia.net Hadoop is emerging as the framework of choice while dealing with big data. It can no longer be classified as a specialized skill, rather it has to become the enterprise data hub of choice and relational database to deliver on its promise of being the go to technology for Big Data Analytics.

Hadoop 52

Hadoop BI Big Data Big Data Tools 52

ProjectPro

NOVEMBER 14, 2015

As we step into the latter half of the present decade, we can’t help but notice the way Big Data has entered all crucial technology-powered domains such as banking and financial services, telecom, manufacturing, information technology, operations, and logistics. That is where Apache Hadoop and Apache Spark come in.

Hadoop 52

Hadoop Project Big Data Healthcare 52

ProjectPro

OCTOBER 15, 2014

Directly leverages SQL and is easy to learn for database experts. Get FREE Access to Data Analytics Example Codes for Data Cleaning, Data Munging, and Data Visualization Hadoop technology is the buzz word these days but most of the IT professionals still are not aware of the key components that comprise the Hadoop Ecosystem.

Hadoop 52

Hadoop Unstructured Data Java SQL 52

ProjectPro

JUNE 6, 2015

How can business intelligence scale and analyse the growing data heap? Business Intelligence (BI) combines human knowledge, technologies like distributed computing, and Artificial Intelligence, and big data analytics to augment business decisions for driving enterprise’s success.

Business Intelligence 40

Business Intelligence Big Data BI Hadoop 40

DareData

JANUARY 30, 2023

They can be simple or complex, and they can involve multiple steps, technologies or formats such as CSV, Tabular or JSON formats. 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.

Data Engineering 52

Data Engineering Data Engineer NoSQL Engineering 52

Knowledge Hut

JULY 24, 2023

Get ready to discover fascinating insights, uncover mind-boggling facts, and explore the transformative potential of cutting-edge technologies like blockchain, cloud computing, and artificial intelligence. To kick-start your career in database management, you can take the best database courses.

Database 52

Database NoSQL Management Relational Database 52

ProjectPro

MARCH 19, 2015

Big Data NoSQL databases were pioneered by top internet companies like Amazon, Google, LinkedIn and Facebook to overcome the drawbacks of RDBMS. RDBMS is not always the best solution for all situations as it cannot meet the increasing growth of unstructured data.

NoSQL 49

NoSQL Big Data SQL Database-centric 49

Knowledge Hut

DECEMBER 26, 2023

Data Engineering is typically a software engineering role that focuses deeply on data – namely, data workflows, data pipelines, and the ETL (Extract, Transform, Load) process. These data have been accessible to us because of the advanced and latest technologies which are used in the collection of data.

Data Engineering 98

Data Engineering Data Engineer Engineering Pipeline-centric 98

Knowledge Hut

JULY 24, 2023

As data generation continues to skyrocket, the demand for real-time decision-making, data processing, and analysis increases. Recently, the advent of stream processing has unlocked the door for a new era in database technology. According to recent studies, the global database market will grow from USD 63.4

SQL 52

SQL Database Process NoSQL 52

AltexSoft

JUNE 26, 2023

Find sources of relevant data. Choose data collection methods and tools. Decide on a sufficient data amount. Set up data storage technology. Below, we’ll elaborate on each step one by one and share our experience of data collection. Key differences between structured, semi-structured, and unstructured data.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

Knowledge Hut

MARCH 20, 2024

One of the most rapidly expanding and in-demand sectors to work in is information technology. Technology is advancing so quickly that there will always be chances in tech industries like software engineering for employment and financial gain. Data engineers must know about big data technologies like Hive, Spark, and Hadoop.

Software Engineer 52

Software Engineer Software Engineering Engineering Java 52

Rockset

JUNE 7, 2022

Editor Databases are a key architectural component of many applications and services. Traditionally, organizations have chosen relational databases like SQL Server, Oracle , MySQL and Postgres. Relational databases use tables and structured languages to store data.

MongoDB 52

MongoDB NoSQL Non-relational Database Relational Database 52

Knowledge Hut

MARCH 19, 2024

AWS's computing power, storage, database management , and artificial intelligence technologies have benefited businesses of all sizes, from startups to multinational corporations. It is the perfect fit for complex daily database requirements that are OLTP/transactional.

AWS 52

AWS Amazon Web Services Hospitality Cloud Computing 52

Workfall

MARCH 21, 2023

It is highly available, scalable, and distributed, and it supports: SQL querying from client devices GraphQL ACID transactions WebSocket connections Both structured and unstructured data Graph querying Full-text indexing Geospatial querying Row permission-based access SurrealQL is an out-of-the-box SQL-style query language included with SurrealDB.

PostgreSQL 68

PostgreSQL NoSQL Database Unstructured Data 68

U-Next

AUGUST 25, 2022

An open-spurce NoSQL database management program, MongoDB architecture, is used as an alternative to traditional RDMS. MongoDB is built to fulfil the needs of modern apps, with a technical base that allows you through: The document data model demonstrates the most effective approach to work with data. Introduction.

MongoDB 40

MongoDB Architecture NoSQL MySQL 40

AltexSoft

DECEMBER 23, 2022

This is because the target system can perform data transformation and loading in parallel, which speeds up the process. A project requires large amounts of both structured and unstructured data , such as data generated by sensors, GPS trackers, and video recorders. Partial data extraction with update notifications.

Process 52

Process Building Raw Data Data Lake 52

ProjectPro

JANUARY 19, 2022

As a result, the role of data engineer has become increasingly important in the technology industry. Data engineering is a new and ever-evolving field that can withstand the test of time and computing developments. Data engineers will be in high demand as long as there is data to process. According to the 2020 U.S.

Data Engineering 52

Data Engineering Data Engineer Engineering Scala 52

AltexSoft

MAY 14, 2021

And most of this data has to be handled in real-time or near real-time. Variety is the vector showing the diversity of Big Data. This data isn’t just about structured data that resides within relational databases as rows and columns. Major Big Data analytics tools and services. NoSQL databases.

Big Data 78

Big Data Data Analytics IT NoSQL 78

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

Knowledge Hut

SEPTEMBER 6, 2023

Over the past decade, the IT world transformed with a data revolution. Back when I studied Computer Science in the early 2000s, databases like MS Access and Oracle ruled. 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.

Database 52

Database Certification MongoDB MySQL 52

AltexSoft

SEPTEMBER 21, 2023

This endeavor would unwittingly plant the seeds for Elasticsearch, a technology that today drives data search and analytics for businesses around the globe. But like any technology, it has its share of pros and cons. As a result, Elasticsearch is exceptionally efficient in managing structured and unstructured data.

Engineering 52

Engineering NoSQL Programming Language Java 52

ProjectPro

OCTOBER 28, 2015

Sqoop in Hadoop is mostly used to extract structured data from databases like Teradata, Oracle, etc., and Flume in Hadoop is used to sources data which is stored in various sources like and deals mostly with unstructured data. The complexity of the big data system increases with each data source.

ETL Tools 52

ETL Tools Hadoop Relational Database Unstructured Data 52

AltexSoft

JULY 29, 2022

The biggest star of the Big Data world, Hadoop was named after a yellow stuffed elephant that belonged to the 2-year son of computer scientist Doug Cutting. The toy became the official logo of the technology, used by the major Internet players — such as Twitter, LinkedIn, eBay, and Amazon. The Hadoop toy. Fault tolerance.

Hadoop 59

Hadoop Big Data Google Cloud NoSQL 59

AltexSoft

JUNE 7, 2021

MapReduce performs batch processing only and doesn’t fit time-sensitive data or real-time analytics jobs. Data engineers who previously worked only with relational database management systems and SQL queries need training to take advantage of Hadoop. Data management and monitoring options.

Big Data Tools 98

Big Data Tools Hadoop Big Data Database-centric 98

ProjectPro

NOVEMBER 5, 2014

MongoDB NoSQL database is used in the big data stack for storing and retrieving one item at a time from large datasets whereas Hadoop is used for processing these large data sets. For organizations to keep the load off MongoDB in the production database, data processing is offloaded to Apache Hadoop.

MongoDB 40

MongoDB Hadoop NoSQL Big Data 40

AltexSoft

NOVEMBER 10, 2021

Prior to the recent advances in data management technologies, there were two main types of data stores companies could make use of, namely data warehouses and data lakes. Data warehouse. Traditional data warehouse platform architecture. websites, etc.

Architecture 52

Architecture Data Lake Data Warehouse Metadata 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

Edureka

FEBRUARY 7, 2023

8) Difference between ADLS and Azure Synapse Analytics Fig: Image by Microsoft Highly scalable and capable of ingesting and processing enormous amounts of data, Azure Data Lake Storage Gen2 and Azure Synapse Analytics are both available (on a Peta Byte scale). 21) What are databases with multiple models?

Data Engineering 52

Data Engineering Data Engineer Engineering Data Lake 52

ProjectPro

JULY 30, 2021

Companies need engineers that can help them transition over to Cloud Computing or senior engineers who can maintain and innovate on the already established Cloud Computing technology. Building data storage and computing architecture locally were getting more expensive during the advent of Big Data technologies.

Cloud Computing 40

Cloud Computing Cloud Amazon Web Services AWS 40

ProjectPro

AUGUST 11, 2021

They store current and historical data in one place and are used to create analytical reports for workers throughout the enterprise." This means that a data warehouse is a collection of technologies and components that are used to store data for some strategic use. This layer should support both SQL and NoSQL queries.

Data Lake 52

Data Lake Data Warehouse Cloud Hadoop 52

ProjectPro

JULY 27, 2021

This blog is your one-stop solution for the top 100+ Data Engineer Interview Questions and Answers. In this blog, we have collated the frequently asked data engineer interview questions based on tools and technologies that are highly useful for a data engineer in the Big Data industry.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

ProjectPro

MARCH 16, 2015

The sum total of data related to the patient and their well-being constitutes the “Big Data” problem in the healthcare industry.Big Data Analytics has actually become an on the rise and crucial problem in healthcare informatics as well. Provide storage for billions and trillions of unstructured data sets.

Healthcare 40

Healthcare Big Data Project Hospitality 40

AltexSoft

NOVEMBER 23, 2021

Multiple BI tools require access to the same data sources. Let’s take a look at real-world use cases to see how companies operating in different industries leverage data virtualization technology. Data virtualization platforms can link to different data sources including.

Process 69

Process Data Lake Metadata Data Warehouse 69

Knowledge Hut

DECEMBER 26, 2023

You can also gain knowledge and certification on big data in detail through Big Data certification online courses. Top Big Data Books for Beginners 1. Big Data: Concepts, Technology and Architecture For data scientists, engineers, and database managers, Big Data is the best book to learn big data.

Big Data 75

Big Data Data Mining Business Intelligence Machine Learning 75