Striim

MARCH 21, 2025

Bi-directional data flow between the legacy system and the cloud system allows you to have users on both sides. You end up having data flowing in the right format for your cloud analytics solution. This unlimited testing minimizes your risks. The time pressure is gone, and you can be comfortable with your move to the cloud.

Cloud 52

Cloud Database Architecture BI 52

Snowflake

FEBRUARY 7, 2023

Next-gen product analytics is now warehouse-native, an architectural approach that allows for the separation of code and data. In this model, providers of next-gen product analytics maintain code for the analytical application as a connected app, while customers manage the data in their own cloud data platform.

BI 83

BI Building ETL Tools Data Warehouse 83

ProjectPro

JUNE 6, 2025

AWS DevOps Real-Time Projects Below are two AWS DevOps real-time project ideas for those who want to work with real-time data using AWS DevOps- Real-Time IoT Data Analytics Using AWS IoT Tools And Technologies: AWS IoT Core, Amazon Kinesis or Amazon S3, AWS QuickSight/ Tableau/ Power BI, Machine Learning. PREVIOUS NEXT <

AWS 61

AWS Project Medical Deep Learning 61

Christophe Blefari

JANUARY 7, 2023

Introducing ADBC: Database Access for Apache Arrow — When I see "minimal-overhead alternative to JDBC/ODBC for analytical applications" I'm instantly in. Qlik and Talend are two old BI giants. I think this is even relevant to data world. You can also listen a related podcast about Arrow vision.

Data 130

Data Data Science Kafka BI 130

Data Engineering Podcast

AUGUST 27, 2021

In this episode Dan DeMers, Cinchy’s CEO, explains how their concept of a "Dataware" platform eliminates the need for costly and error prone integration processes and the benefits that it can provide for transactional and analytical application design. No more scripts, just SQL. No more scripts, just SQL.

Data Integration 100

Data Integration Architecture Data Warehouse Data Lake 100

Cloudera

NOVEMBER 7, 2023

Most traditional analytics applications like Hive, Spark, Impala, YARN etc. Hive, Spark, Impala, YARN, BI tools with S3 connectors can interact with Ozone using the s3a protocol. Protocols provided by Ozone: ofs ofs is a Hadoop Compatible File System (HCFS) protocol.

Systems 105

Systems Hadoop Unstructured Data Media 105

ProjectPro

JUNE 6, 2025

The company targets to deliver values to its customers through the free SaaS based analytics applications so that it can build credibility with the clients to encourage them to buy more. The products and services of Cloudera are changing the economics of big data analysis , BI, data processing and warehousing through Hadooponomics.

Big Data 40

Big Data Hadoop Business Analyst Data Analytics 40

Towards Data Science

APRIL 26, 2023

As data practitioners we want (and love) to build applications on top of our data as seamlessly as possible. Whether you work in BI, Data Science or ML all that matters is the final application and how fast you can see it working end-to-end. A lightinign fast analytics app built with our system. Image from the authors.

Engineering 96

Engineering Data Lake AWS BI 96

Cloudera

NOVEMBER 2, 2020

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. Analytics storage engine for huge volumes of fast arriving data. Interactive query engine for fast BI over huge volumes of data. Spark Streaming.

Data Warehouse 97

Data Warehouse Kafka Lambda Architecture Telecommunication 97

Snowflake

AUGUST 14, 2024

It streamlines the development of intuitive, self-serve analytics applications for business users, while providing industry-leading accuracy. Historically, business users have primarily relied on BI dashboards and reports to answer their data questions.

BI 52

BI Government SQL Analytics Application 52

Cloudera

FEBRUARY 8, 2024

Materialized views are valuable for accelerating common classes of business intelligence (BI) queries that consist of joins, group-bys and aggregate functions. Such a query pattern is quite common in BI queries. Apache Iceberg forms the core foundation for Cloudera’s Open Data Lakehouse with the Cloudera Data Platform (CDP).

Metadata 91

Metadata Data Warehouse BI AWS 91

Data Science Blog: Data Engineering

NOVEMBER 15, 2023

In addition to Business Intelligence (BI), Process Mining is no longer a new phenomenon, but almost all larger companies are conducting this data-driven process analysis in their organization. This aspect can be applied well to Process Mining, hand in hand with BI and AI.

Architecture 52

Architecture Database-centric Process BI 52

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 Storage 52

ProjectPro

JUNE 6, 2025

Introduction to Big Data Big data combines structured, semi-structured, and unstructured data collected by organizations to glean valuable insights and information using machine learning, predictive modeling , and other advanced analytical applications. Data is visualized through meaningful charts, plots, and graphs.

Big Data 45

Big Data Big Data Skills Scala Hadoop 45

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

Rockset

JUNE 21, 2022

We’re excited to announce that Rockset’s new connector with Snowflake is now available and can increase cost efficiencies for customers building real-time analytics applications. What’s Needed for Real-Time Analytics? These real-time, user-facing applications include personalization , gamification or in-app analytics.

Kafka 52

Kafka Data Warehouse BI Analytics Application 52

Cloudera

FEBRUARY 9, 2021

A typical approach that we have seen in customers’ environments is that ETL applications pull data with a frequency of minutes and land it into HDFS storage as an extra Hive table partition file. In this way, the analytic applications are able to turn the latest data into instant business insights. Design Detail.

Data Warehouse 72

Data Warehouse Cloud Kafka Cloud Storage 72

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

ProjectPro

JUNE 6, 2025

It is an alternative to business intelligence and data visualization tools like Microsoft's Power BI and Tableau. Kinesis Video streams: This helps you to stream videos in real-time from hundreds of camera devices to the AWS cloud, where you can watch, store ML operations, real-time analytics, and get insights.

AWS 40

AWS Data Engineering Data Engineer Engineering 40

Cloudera

JUNE 16, 2022

Building real-time data analytics pipelines is a complex problem, and we saw customers struggle using processing frameworks such as Apache Storm, Spark Streaming, and Kafka Streams. . SSB can materialize the results from a streaming SQL query to a persistent view of the data that can be read via a REST API.

Kafka 88

Kafka Manufacturing Data Lake SQL 88

Rockset

MAY 17, 2022

Complex SQL queries have long been commonplace in business intelligence (BI). Or a market news provider that needs to monitor and ensure that its financial customers are getting accurate, relevant updates within the narrow windows for profitable trades. Hive implemented an SQL layer on Hadoop’s native MapReduce programming paradigm.

SQL 52

SQL NoSQL Hadoop MongoDB 52

Cloudera

MARCH 6, 2018

This leads to extra cost, effort, and risk to stitch together a sub-optimal platform for multi-disciplinary, cloud-based analytics applications. Instead, they have separate data stores and inconsistent (if any) frameworks for data governance, management, and security. Further, much of the value of cloud is for elastic workloads.

Cloud 40

Cloud Metadata Big Data Analytics Application 40

Cloudera

DECEMBER 7, 2017

Now we are releasing the reference architecture for you build your own self-managed SDX foundation for all your cloud-based data and analytics applications. We announced SDX at Strata New York in September 2017. Best of all, SDX is part of Cloudera’s core platform, not an expensive add-on.

Management 40

Management Building Government BI 40

Knowledge Hut

JUNE 26, 2023

Business intelligence solutions like as Power BI, Tableau, and Looker may assist companies in mitigating operational risk and achieving maximum efficiency in terms of operations enablement by assisting businesses in making choices that are supported by data.

Data Engineering 98

Data Engineering Data Engineer Coding Project 98

Rockset

AUGUST 18, 2020

In the world of batch analytics and BI dashboards you knew exactly what data you needed and what type of questions your business was asking - which gave you the luxury of setting up all sorts of pipelines to format the data exactly as needed, create materialized views, optimize the queries.

Data Lake 40

Data Lake Data Schemas Kafka BI 40

Rockset

DECEMBER 9, 2021

Disclaimer: Rockset is a real-time analytics database and one of the pieces in the modern real-time data stack So What is Real-Time Data (And Why Can’t the Modern Data Stack Handle It)? Real-time data streams typically power analytical or data applications whereas batch systems were built to power static dashboards.

Transportation 52

Transportation BI SQL Data Warehouse 52

AltexSoft

SEPTEMBER 23, 2021

The main purpose of a DW is to enable analytics: It is designed to source raw historical data, apply transformations, and store it in a structured format. This type of storage is a standard part of any business intelligence (BI) system, an analytical interface where users can query data to make business decisions.

Architecture 52

Architecture Data Lake Unstructured Data Data Warehouse 52

AltexSoft

OCTOBER 21, 2022

Hadoop fits heavy, not time-critical analytics applications that generate insights for long-term planning and strategic decisions. The Good and the Bad of Power BI Data Visualization. Hadoop works with batches while Kafka deals with streams, but all the same, the similarities are obvious. Kafka vs ETL.

Kafka 93

Kafka Hadoop ETL Tools Java 93

Knowledge Hut

JUNE 16, 2023

Top Hiring Companies Companies such as Tata Consultancy Services, Capgemini, USEReady, Dell Technologies, Accenture, Wipro, Hewlett Packard Enterprises (HPE), IBM, Visual BI solutions, etc., are regularly hiring Business Intelligence analysts. regularly hire Data Engineers in India.

Data Analytics 52

Data Analytics Business Analyst Consulting Banking 52

Rockset

OCTOBER 4, 2022

Streaming data feeds many real-time analytics applications, from logistics tracking to real-time personalization. Change data capture (CDC) streams from OLTP databases, which may provide sales, demographic or inventory data, are another valuable source of data for real-time analytics use cases.

MySQL 52

MySQL Kafka Aggregated Data Data Warehouse 52

Edureka

JULY 3, 2024

This makes the data ready for consumption by BI tools, analytics applications, or other systems. Publish: Transformed data is then published either back to on-premises sources like SQL Server or kept in cloud storage. Manage Workflow: ADF manages these processes through time-sliced, scheduled pipelines.

Pipeline-centric 52

Pipeline-centric Data Lake Database-centric Data Pipeline 52

Cloudera

MAY 16, 2018

Arcadia Enterprise runs within the Cloudera data platform and enables business intelligence (BI) and rich visual analytic applications to be built for hundreds of business users working on data in Hadoop.

Data Lake 42

Data Lake Electronics Media Unstructured Data 42

Knowledge Hut

MARCH 15, 2024

You will acquire the skills necessary to combine, process, and organize data from different structured and unstructured data sources into frameworks appropriate for constructing analytics applications that make use of Microsoft Azure data services.

Certification 52

Certification Cloud Computing Algorithm SQL 52

ProjectPro

MAY 20, 2015

The company targets to deliver values to its customers through the free SaaS based analytics applications so that it can build credibility with the clients to encourage them to buy more. The products and services of Cloudera are changing the economics of big data analysis , BI, data processing and warehousing through Hadooponomics.

Big Data 40

Big Data Hadoop Business Analyst Data Analytics 40

Rockset

FEBRUARY 9, 2021

Because it integrates easily with S3, is serverless, and uses a familiar language, Athena has become the default service for most business intelligence (BI) decision makers to query the large amounts of (usually streaming) data coming into their object stores.

Data Lake 40

Data Lake Business Intelligence SQL Data 40

AltexSoft

JULY 18, 2023

It has in-memory computing capabilities to deliver speed, a generalized execution model to support various applications, and Java, Scala, Python, and R APIs. Spark Streaming enhances the core engine of Apache Spark by providing near-real-time processing capabilities, which are essential for developing streaming analytics applications.

Big Data 52

Big Data Data Process Process Hadoop 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. These analytic projects will take you through everything you need to know as a data analyst and how to build and deploy an ETL pipeline to combine it with the analytics application.

Portfolio 40

Portfolio Certification Education Data 40