Cloudera

NOVEMBER 2, 2020

This is resulting in advancements of what is provided by the technology, and a resulting shift in the art of the possible. It has the key elements of fast ingest, fast storage, and immediate querying for BI purposes. These include stream processing/analytics, batch processing, tiered storage (i.e. Spark Streaming. What’s Next?

Data Warehouse 97

Data Warehouse Kafka Lambda Architecture Telecommunication 97

Knowledge Hut

DECEMBER 26, 2023

BI encourages using historical data to promote fact-based decision-making instead of assumptions and intuition. What is Business Intelligence (BI)? Business intelligence (BI) is the collective name for a set of processes, systems, and technologies that turn raw data into knowledge that can be used to operate enterprises profitably.

Business Intelligence 52

Business Intelligence BI Data Mining Data Analysis 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

Knowledge Hut

JUNE 26, 2023

Before working on these initiatives, you should be conversant with topics and technologies. Top 4 Data Engineering Project Ideas: Beginner & Final Year Students Becoming an expert data engineer necessitates familiarity with the best practices and cutting-edge technologies in your field.

Data Engineering 98

Data Engineering Data Engineer Coding Project 98

AltexSoft

OCTOBER 21, 2022

Kafka can continue the list of brand names that became generic terms for the entire type of technology. The technology was written in Java and Scala in LinkedIn to solve the internal problem of managing continuous data flows. Similar to other popular open-source technologies, Kafka has a vast community of users and contributors.

Kafka 93

Kafka Hadoop Big Data ETL Tools 93

U-Next

AUGUST 23, 2022

A rapidly expanding data visualization tool called Tableau Software is creating a stir within Business Intelligence (BI) sector. What distinguishes Tableau and Power BI from one another? In contrast, Power BI’s high degree of integration will enable us to create effective dashboards from an executive perspective.

BI 52

BI Amazon Web Services Database Business Intelligence 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

Rockset

DECEMBER 9, 2021

In this article, I’ll also outline: What are the five unique technical characteristics of real-time data; What are the four technology requirements of the modern real-time data stack; And what are the key solutions you need to deploy in your modern real-time data stack. So BI did not democratize access to analytics.

Transportation 52

Transportation BI SQL Database 52

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 hub architecture. Source: marklogic.com.

Architecture 52

Architecture Data Lake Unstructured Data Data Warehouse 52

Knowledge Hut

JUNE 16, 2023

Let’s look into the exciting world of Data Analytics Careers in this digital age! With technological developments every day, the data analytics career is predicted to be in high demand in the upcoming years. With the help of data analytics, businesses get actionable insight to compete with others.

Data Analytics 52

Data Analytics Business Analyst Consulting Business Intelligence 52

Knowledge Hut

MARCH 15, 2024

To thrive in the IT industry, one must be able to keep up with the swift advancements in technology. Obtaining a certification is a great way to keep up with the most recent trends and learn about the newest developments in technology. Furthermore, certifications in Microsoft Azure provide excellent job options.

Cloud Computing 52

Cloud Computing Certification Algorithm SQL 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

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

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

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

ProjectPro

APRIL 19, 2021

These reports can be in the form of PowerPoint Decks, Excel Dashboards, or a report from any visualization tool like Tableau, Power BI, or QlikView. When working as a data analyst learning will be a daily thing because the analytics industry is moving at a fast pace.

Portfolio 40

Portfolio Data Certification Data Analytics 40

U-Next

AUGUST 26, 2022

Due to this, our Data Consultants advise highly data-driven businesses not to limit themselves to descriptive analytics alone but instead to integrate it with other forms of Data Analytics. Analytical Diagnostics. S Global Corporation can see chances for repeat business using advanced analytics and sales trends.

Data Analytics 40

Data Analytics Insurance Transportation Healthcare 40

ProjectPro

MAY 31, 2021

This blog lists over 20 big data projects you can work on to showcase your big data skills and gain hands-on experience in big data tools and technologies. The use of Spark SQL to store the data and Apache Hive to process the data, along with a few applications of machine learning, can build the required recommendation system.

Big Data 52

Big Data Coding Project Hadoop 52