AltexSoft

OCTOBER 21, 2022

Kafka can continue the list of brand names that became generic terms for the entire type of technology. In this article, we’ll explain why businesses choose Kafka and what problems they face when using it. The technology was written in Java and Scala in LinkedIn to solve the internal problem of managing continuous data flows.

Kafka 93

Kafka Hadoop Big Data ETL Tools 93

AltexSoft

SEPTEMBER 23, 2021

We’ll also analyze some of the data hub products existing in the market to explore how this technology works and what it actually can do. It’s not a single technology, but rather an architectural approach that unites storages, data integration and orchestration tools. What is Data Hub? Data access layer: data querying.

Architecture 52

Architecture Data Lake Unstructured Data Data Warehouse 52

Rockset

MAY 17, 2022

Complex SQL queries have long been commonplace in business intelligence (BI). GraphQL’s main analytics shortcoming is its lack of expressive power to join two disparate datasets based on the value of specific fields in those two datasets. Most analytical queries need this ability to join multiple data sources at query time.

SQL 52

SQL NoSQL Hadoop MongoDB 52

Cloudera

DECEMBER 7, 2017

Cloud service providers now offer a plethora of “house brand” analytics services, some brand new, some re-purposed versions of older technologies. Yet there is often a dark side to using public cloud service providers’ analytics offerings in the cloud, too. We announced SDX at Strata New York in September 2017.

Building 40

Building Management Government BI 40

U-Next

MARCH 22, 2022

Upskilling in Business Analytics provides a golden opportunity for mid-career professionals who feel stuck in their professional journey and want to transform their careers. Learners can improve their decision-making and problem-solving abilities by utilizing emerging technologies and tools.

Business Analyst 52

Business Analyst Business Intelligence Programming Certification 52

Rockset

FEBRUARY 2, 2022

Let’s explore five ways to run MongoDB analytics, along with the pros and cons of each method. 1 – Query MongoDB Directly The first and most direct approach is to run your analytical queries directly against MongoDB. There are quite a few of these on the market, with each trying to enable business intelligence (BI) on MongoDB.

MongoDB 52

MongoDB NoSQL Data Warehouse BI 52

ProjectPro

MAY 20, 2015

According to NASSCOM, the global big data analytics market is anticipated to reach $121 billion by 2016. Another research report by IDC predicts 27% compound annual growth rate for big data services and technologies by end of 2017 which equals 6 times the CAGR of the IT market as a whole.

Big Data 40

Big Data Hadoop Business Analyst Data Analytics 40

Knowledge Hut

JUNE 30, 2023

It covers popular technologies such as Apache Kafka, Apache Storm, and Apache Hadoop, giving users practical advice on developing and executing effective data pipelines. With helpful illustrations and thorough explanations, it assists readers in comprehending how to use Spark for big data processing and analytics applications.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Warehouse 52

U-Next

AUGUST 23, 2022

Tableau serves as a visual framework for business intelligence and analytics, assisting users in watching, observing, comprehending, and making choices with various data types. A rapidly expanding data visualization tool called Tableau Software is creating a stir within Business Intelligence (BI) sector.

BI 52

BI Amazon Web Services Database Business Intelligence 52

U-Next

SEPTEMBER 29, 2022

During the forecast period, the global Workforce Analytics Market is expected to grow at a Compound Annual Growth Rate (CAGR) of 15.3% Enterprises are facing the immense challenge of analyzing HR data structure in real-time, driving a rapid increase in the demand for advanced analytical tools and analytics applications. .

IT 52

IT Recruitment Data Analysis Consulting 52

Cloudera

MAY 16, 2018

To respond to their respective business, operational, and regulatory requirements in a complex and competitive marketplace , each group needs its own set of subject matter expertise and best of breed technology platforms.

Data Lake 42

Data Lake Electronics Media Unstructured Data 42

phData: Data Engineering

JULY 18, 2023

Perhaps the largest roadblock of this data-driven utopia is the continued reliance on a patchwork of legacy, on-premise technologies like Teradata, Netezza, Oracle, etc., The combination of these technologies has become collectively known as the Modern Data Stack. Why Migrate to a Modern Data Stack?

Data Warehouse 52

Data Warehouse Pipeline-centric Government Data 52

Knowledge Hut

JULY 26, 2023

They are commonly used in applications such as data warehousing, business intelligence, and analytics. It is widely utilized for its great scalability, fault tolerance, and quick write performance, making it ideal for large-scale data storage and real-time analytics applications. Spatial Database (e.g.-

Database 52

Database NoSQL MongoDB Telecommunication 52

ProjectPro

JULY 15, 2021

Cloud computing is the technology that provides on-demand computing resources or hosted services to the end-users over the networking channel, which is usually the Internet. These resources and services can include databases, software applications, networks, servers, and others. What is Cloud Computing?

Cloud Computing 40

Cloud Computing Cloud Project Banking 40

AltexSoft

JULY 18, 2023

This article will expose Apache Spark architecture, assess its advantages and disadvantages, compare it with other big data technologies, and provide you with the path to learning this impactful instrument. Understanding them can help you decide whether Spark is the right choice for your specific needs.

Big Data 52

Big Data Data Process Process Hadoop 52

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. Learn more about Big Data Tools and Technologies with Innovative and Exciting Big Data Projects Examples.

Big Data 52

Big Data Hadoop Relational Database AWS 52