Rockset

MAY 17, 2022

We'll be publishing more posts in the series in the near future, so subscribe to our blog so you don't miss them! More application code not only takes more time to create, but it almost always results in slower queries. There are some myths about SQL databases , but they are based on legacy relational systems from the 1990s.

SQL 52

SQL NoSQL Hadoop MongoDB 52

Rockset

MARCH 10, 2022

We'll be publishing more posts in the series in the near future, so subscribe to our blog so you don't miss them! Analytical queries could be accelerated by caching heavily-accessed read-only data in RAM or SSDs. Get faster analytics on fresher data, at lower costs, by exploiting indexing over brute-force scanning.

Data Analytics 52

Data Analytics Data Warehouse Medical MySQL 52

Knowledge Hut

JULY 26, 2023

Database applications also help in data-driven decision-making by providing data analysis and reporting tools. In this blog, we will deep dive into database system applications in DBMS, and their components and look at a list of database applications. What are Database Applications? Spatial Database (e.g.-

Database 52

Database NoSQL Telecommunication MongoDB 52

ProjectPro

FEBRUARY 16, 2023

If you are still wondering whether or why you need to master SQL for data engineering, read this blog to take a deep dive into the world of SQL for data engineering and how it can take your data engineering skills to the next level. If your database is cloud-based, using SQL to clean data is far more effective than scripting languages.

Data Engineering 52

Data Engineering Data Engineer SQL Engineering 52

Cloudera

NOVEMBER 7, 2023

Navigating this intricate maze of data can be challenging, and that’s why Apache Ozone has become a popular, cloud-native storage solution that spans any data use case with the performance needed for today’s data architectures. Most traditional analytics applications like Hive, Spark, Impala, YARN etc.

Systems 100

Systems Hadoop Unstructured Data Media 100

ProjectPro

MAY 20, 2015

There are several big data and business analytics companies that offer a novel kind of big data innovation through unprecedented personalization and efficiency at scale. Which big data analytic companies are believed to have the biggest potential?

Big Data 40

Big Data Hadoop Business Analyst Unstructured Data 40

ProjectPro

FEBRUARY 11, 2021

Implement statistical analysis and machine learning into highly available and high performance production level systems to provide ease of access to users. Translate the machine learning models defined by data scientists from environments like Python and R notebooks to analytic applications. Handling exceptions.

Machine Learning 40

Machine Learning Engineering Programming Language Portfolio 40

Rockset

OCTOBER 26, 2023

That’s why JetBlue innovates with real-time analytics and AI, using over 15 machine learning applications in production today for dynamic pricing, customer personalization, alerting applications, chatbots and more. Rockset provides the speed and scale required of ML applications accessed daily by over 2,000 employees at JetBlue.

Machine Learning 64

Machine Learning Data Science Architecture Data Warehouse 64

Cloudera

MARCH 6, 2018

People are gravitating to the analytics services of the large public cloud providers because the “house-brand” offerings seem to be the easiest choice. This leads to extra cost, effort, and risk to stitch together a sub-optimal platform for multi-disciplinary, cloud-based analytics applications.

Cloud 40

Cloud Metadata Big Data AWS 40

Cloudera

AUGUST 13, 2021

A global oil and gas company collects, transforms, and distributes over hundreds terabytes of desktop, server, and application log data to their SIEM per day. As the company evolves into a hybrid and multi-cloud strategy, they need to start collecting applications, servers, and network logs from the cloud.

Data Pipeline 108

Data Pipeline Data Lake ETL Tools Unstructured Data 108

Cloudera

NOVEMBER 13, 2017

As the market moves toward cloud-based big data and analytics, three qualities emerge as vital for success. Cloud IaaS facilitates resource self-service provisioning, eliminating the hassles of procurement and deployment on-premises. Make sure any cloud-based analytics service meets these criteria.

Cloud 40

Cloud Big Data Metadata Machine Learning 40

Cloudera

SEPTEMBER 15, 2022

In this blog post, we will talk about a single Ozone cluster with the capabilities of both Hadoop Core File System (HCFS) and Object Store (like Amazon S3). Interoperability of the same data for several workloads: multi-protocol access. Ranger policies enable authorization access to Ozone resources (volume, bucket, and key).

Systems 86

Systems Hadoop Metadata Telecommunication 86

Rockset

MAY 3, 2023

In scenarios involving analytics on massive data streams, we’re often asked the maximum throughput and lowest data latency Rockset can achieve and how it stacks up to other databases. In this blog, we’ll walk through the benchmark framework, configuration and results. Rockset achieved up to 4x higher throughput and 2.5x

Data Ingestion 59

Data Ingestion Kafka Database Architecture 59

Rockset

MARCH 15, 2021

The Demands of Real-Time Analytics Real-time analytics applications have specific demands (i.e., and your solution will only be able to provide valuable real-time analytics if you are able to meet them. Thus queries can access data in the memory itself and don’t have to wait until it is written to the disk.

MongoDB 40

MongoDB Data Ingestion Analytics Application Kafka 40

phData: Data Engineering

MAY 11, 2023

Practices centered on software engineering principles can create a barrier to entry for teams with skilled data wranglers looking to take their infrastructure to the next level with cloud-native tools like Matillion for the Snowflake Data Cloud. That begs the question, if it is so easy to learn, “Why formalize a concept like ZDLC?”

Coding 52

Coding Software Engineer Software Engineering Government 52

Cloudera

NOVEMBER 2, 2020

Optimized access to both full fidelity raw data and aggregations. Optimized access to both current data and historical data. Time Series and Event Analytics Specialized RTDW. Cloudera offers a platform, Cloudera Data Platform (CDP), for building end-to-end data applications in both the public and private cloud.

Data Warehouse 91

Data Warehouse Kafka Lambda Architecture Telecommunication 91

Cloudera

DECEMBER 7, 2017

Cloud promises many advantages as an environment for machine learning and analytics. Cloud makes it fast and easy to spin up resources for new applications. Cloud offers elasticity of those resources to efficiently support transient analytics workloads and data pipelines.

Building 40

Building Management Government BI 40

Cloudera

NOVEMBER 8, 2022

It enables cloud-native applications to store and process mass amounts of data in a hybrid multi-cloud environment and on premises. These could be traditional analytics applications like Spark, Impala, or Hive, or custom applications that access a cloud object store natively. Conclusion.

Metadata 80

Metadata Algorithm Hadoop Cloud 80

Cloudera

APRIL 2, 2019

Cloudera customers who want more flexibility in how and where they run their applications can benefit from Intel Optane DC persistent memory as well. A key characteristic of an enterprise data cloud is its ability to run multiple workloads on shared data without encountering “noisy neighbor” problems.

NoSQL 47

NoSQL Google Cloud Hadoop Machine Learning 47

Rockset

DECEMBER 9, 2019

Rockset is a real time analytics engine that allows SQL queries directly on raw data, such as nested JSON and XML. It continuously ingests raw data from multiple sources--data lakes, data streams, databases--into its storage layer and allows fast SQL access from both visualisation tools and analytic applications.

Data Engineering 40

Data Engineering Data Engineer Raw Data Engineering 40

ProjectPro

SEPTEMBER 6, 2021

Are you confused about choosing the best cloud platform for your next data engineering project ? AWS vs. GCP blog compares the two major cloud platforms to help you choose the best one. So, are you ready to explore the differences between two cloud giants, AWS vs. google cloud? Let’s get started!

AWS 52

AWS Amazon Web Services Google Cloud Cloud Storage 52

AltexSoft

OCTOBER 21, 2022

A single cluster can span across multiple data centers and cloud facilities. cloud data warehouses — for example, Snowflake , Google BigQuery, and Amazon Redshift. Another security measure is an audit log to track access. If you are interested in web development, take a look at our blog post on. Large user community.

Kafka 93

Kafka Hadoop ETL Tools Big Data 93

Cloudera

NOVEMBER 9, 2018

Armed with those personal data, cybercrooks could use them to illegally access a victim’s bank account or create a composite of the individual to commit offline crimes such as burglary, extortion, or fraud. Drive real-time processing and analytics to IoT data – both in motion and at rest.

Machine Learning 56

Machine Learning Banking Government Media 56

ProjectPro

MAY 23, 2015

Big Data Analytics Solutions at Walmart Social Media Big Data Solutions Mobile Big Data Analytics Solutions Walmart’ Carts – Engaging Consumers in the Produce Department World's Biggest Private Cloud at Walmart- Data Cafe How Walmart is fighting the battle against big data skills crisis? PB of data every hour.

Big Data 52

Big Data Data Analysis Hadoop Retail 52

ProjectPro

JANUARY 31, 2023

In this blog, we'll dive into some of the most commonly asked big data interview questions and provide concise and informative answers to help you ace your next big data job interview. Hadoop can execute MapReduce applications in various languages, including Java, Ruby, Python, and C++. When to use MapReduce with Big Data.

Big Data 52

Big Data Hadoop AWS Relational Database 52

Cloudera

OCTOBER 12, 2020

We are thrilled to announce that Cloudera has acquired Eventador , a provider of cloud-native services for enterprise-grade stream processing. We believe Eventador will accelerate innovation in our Cloudera DataFlow streaming platform and deliver more business value to our customers in their real-time analytics applications.

Cloud 131

Cloud Process Scala Kafka 131

Cloudera

JUNE 16, 2022

This blog aims to answer two questions as illustrated in the diagram below: How have stream processing requirements and use cases evolved as more organizations shift to “streaming first” architectures and attempt to build streaming analytics pipelines?

Kafka 84

Kafka Manufacturing Data Lake SQL 84

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. Here are some options for collecting data that you can utilize: Connect to an existing database that is already public or access your private database.

Big Data 52

Big Data Coding Project Hadoop 52

Rockset

APRIL 15, 2022

We'll be publishing more posts in the series in the near future, so subscribe to our blog so you don't miss them! So why are their analytics still crawling through in batches instead of real time? It’s probably because their analytics database lacks the features necessary to deliver data-driven decisions accurately in real time.

Analytics Application 52

Analytics Application Data Warehouse Raw Data Kafka 52

phData: Data Engineering

JULY 18, 2023

Imagine a world where all of your data is organized, easily accessible, and routinely leveraged to drive impactful outcomes. With the birth of cloud data warehouses, data applications, and generative AI , processing large volumes of data faster and cheaper is more approachable and desired than ever.

Data Warehouse 52

Data Warehouse Pipeline-centric Government Data 52

Cloudera

NOVEMBER 22, 2021

Explosion of data availability from a variety of sources, including on-premises data stores used by enterprise data warehousing / data lake platforms, data on cloud object stores typically produced by heterogenous, cloud-only processing technologies, or data produced by SaaS applications that have now evolved into distinct platform ecosystems (e.g.,

Government 89

Government Hadoop Data Security Data Warehouse 89