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.

Data Integration 100

Data Integration Architecture Data Warehouse Data Lake 100

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.

Cloud Computing 52

Cloud Computing Algorithm Certification SQL 52

Cloudera

SEPTEMBER 15, 2022

Modern data platforms deliver an elastic, flexible, and cost-effective environment for analytic applications by leveraging a hybrid, multi-cloud architecture to support data fabric, data mesh, data lakehouse and, most recently, data observability. Are there things they should keep in mind?

Data Lake 83

Data Lake Analytics Application Cloud Storage Architecture 83

Rockset

JULY 6, 2022

Similarly, databases are only useful for today’s real-time analytics if they can be both strict and flexible. Traditional databases, with their wholly-inflexible structures, are brittle. So are schemaless NoSQL databases, which capably ingest firehoses of data but are poor at extracting complex insights from that data.

NoSQL 52

NoSQL SQL Systems PostgreSQL 52

Christophe Blefari

MARCH 24, 2023

Hex is a notebook-based analytics application. Cells are at the center of the analytics, they produce outputs than can be used later in other cells on in visualisation. I don't have a lot to say except the fact that we are going in a future with a lot of databases choices. Hex raises $28m in a Venture Round [1].

Lambda Architecture 130

Lambda Architecture Data Pipeline Data SQL 130

Rockset

MAY 17, 2022

That changed when NoSQL databases such as key-value and document stores came on the scene. The designers of these massive, scalable key-value stores or document databases decided that scale and speed were possible only if the queries were simple in nature. As a result, the use cases remained firmly in batch mode.

SQL 52

SQL NoSQL Hadoop MongoDB 52

Rockset

MARCH 24, 2022

Even though the complexity, data shape and data volume are increasing and changing, companies are looking for simpler and faster database solutions. It’s difficult to create data analytics systems that can easily do this while maintaining fast query performance and real-time capabilities.

Non-relational Database 52

Non-relational Database Relational Database Database Data Pipeline 52

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. Why It’s So Hard to Become a Staff Engineer — A feedback to help people bringing the gap between senior and staff.

Data Science 130

Data Science Data BI Kafka 130

Rockset

FEBRUARY 18, 2021

Data latency is the time from when data is produced to when it can be queried, and is a function of how efficiently a database can sustain writes. Query Latency and the Star Schema Benchmark Query latency is the second key measure of real-time analytics performance and is the focus of the rest of this post. Rockset was 9.4x

Analytics Application 52

Analytics Application SQL Database Structured Data 52

Rockset

FEBRUARY 2, 2022

MongoDB is a top database choice for application development. Developers choose this database because of its flexible data model and its inherent scalability as a NoSQL database. MongoDB wasn’t originally developed with an eye on high performance for analytics.

MongoDB 52

MongoDB NoSQL Data Warehouse BI 52

Data Science Blog: Data Engineering

JULY 4, 2022

For fast analytic queries against another size of data, it uses in-memory caching and optimised query execution. It is a parallel processing framework for grouped computers to operate large-scale data analytics applications. This could handle packet and real-time data processing and predictive analysis workloads.

Hadoop 52

Hadoop Big Data Datasets Scala 52

ProjectPro

FEBRUARY 16, 2023

Even Fortune 500 businesses (Facebook, Google, and Amazon) that have created their own high-performance database systems also typically use SQL to query data and conduct analytics. Data engineers can extract data from a table in a relational database using SQL queries like the "SELECT" statement with the "FROM" and "WHERE" clauses.

Data Engineering 52

Data Engineering Data Engineer SQL Engineering 52

Knowledge Hut

JUNE 26, 2023

This project's architecture is essentially composed on five layers: the Data Ingestion layer, the Message broker layer, the Stream processing layer, the Serving database layer, and the Visualisation layer. This dashboard shows real-time charts and graphs that are based on the data that is stored in the database.

Data Engineering 98

Data Engineering Data Engineer Coding Project 98

Rockset

AUGUST 11, 2020

This needed a database that could use a location index to instantaneously find out the best ads for me. No more batch analytics.this is analytics-on-the-fly! The challenge of building analytical applications on your most recent datasets is a tough challenge. Why is that?

Hadoop 52

Hadoop Datasets Banking Analytics Application 52

Knowledge Hut

JUNE 30, 2023

Investigate alternative data storage solutions, such as databases and data lakes. With helpful illustrations and thorough explanations, it assists readers in comprehending how to use Spark for big data processing and analytics applications. Investigate Spark's batch processing, streaming, and machine learning capabilities.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Warehouse 52

Rockset

AUGUST 4, 2021

Although Snowflake is great at querying massive amounts of data, the database still needs to ingest this data. Without performant data ingestion, you run the risk of querying outdated values and returning irrelevant analytics. Import Delays When Snowpipe imports data, it can take minutes to show up in the database and be queryable.

Data Ingestion 40

Data Ingestion Cloud Storage Data Warehouse Data Lake 40

Striim

NOVEMBER 8, 2023

The four data mesh principles aim to solve major difficulties that have plagued data and analytics applications for a long time. Striim continuously reads the operational database transaction logs from disjointed databases in their on-prem data center, continuously syncing data to a unified data layer in the cloud.

Architecture 52

Architecture Generalist Government Datasets 52

Rockset

AUGUST 18, 2020

This means the lines between real-time analytics and real-time analytical applications are now blurring. Live dashboards that alert humans to take actions and online applications that automatically trigger the right actions are both in the realm of real-time analytics.

Data Lake 40

Data Lake Data Schemas BI Kafka 40

Knowledge Hut

JUNE 16, 2023

Roles and Responsibilities Extract data from different sources Evaluate and clean data sets to build complex data pipelines Stitch all the data together Create and expose data stores to analytical applications Salary Range The salary of a Data Engineer is in the range of $132,922 per year. regularly hire Data Engineers in India.

Data Analytics 52

Data Analytics Business Analyst Business Intelligence Consulting 52

U-Next

SEPTEMBER 21, 2022

While people are required to provide context and comprehend intricate circumstances, data science benefits from less inaccuracy, enabling more accurate estimates and data analytics. . Applications of AI in Business Operations . Rule-based . Intelligence . AI-powered. Facial Recognition Technology . Law enforcement .

Insurance 40

Insurance Finance Transportation Machine Learning 40

ProjectPro

JULY 15, 2021

These resources and services can include databases, software applications, networks, servers, and others. You can also exchange images securely utilizing the application. It is recommended to use SQL database for data storage as it comes with built-in security tools and features.

Cloud Computing 40

Cloud Computing Cloud Project Banking 40

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.

Data Warehouse 70

Data Warehouse Cloud Kafka Cloud Storage 70

Towards Data Science

APRIL 3, 2023

From Enormous Data back to Big Data Say you are tasked with building an analytics application that must process around 1 billion events (1,000,000,000) a day. While this might feel far-fetched at first, due to the sheer size of the data, it often helps to step back and think about the intention of the application (what does it do?)

Process 88

Process Data Lake Systems Bytes 88

ProjectPro

APRIL 19, 2021

Collect Data Having clearly defined the business problem, a data analyst determines what data needs to be collected from existing data sources or databases. Develop database querying language skills in SQL and NoSQL. It is often a data analyst’s job to communicate the plan of action to the team. Do not dismiss excel with a sniff.

Portfolio 40

Portfolio Data Finance Certification 40

Monte Carlo

MAY 14, 2024

It bridges the gap between traditional databases and the big data world, providing a platform for complex data transformations and batch processing in environments that require deep data analysis. This combination allows users to use standard SQL statements to manage and query data lakes with the same finesse as traditional databases.

Data Lake 52

Data Lake Metadata Hadoop Data Governance 52

Rockset

OCTOBER 26, 2023

A core enabler of the speed of ML development with BlueML is the flexibility of the underlying database system. With Rockset’s Converged Indexing technology , data is indexed in a search index, columnar store, ANN index and row store for millisecond-latency analytics across a wide range of query patterns.

Machine Learning 64

Machine Learning Data Science Architecture Data Warehouse 64

Knowledge Hut

DECEMBER 26, 2023

Given its status as one of the complete all-in-one analytics and BI systems available currently, the platform requires some getting accustomed to. Some key features include business intelligence, enterprise planning, and analytics application. You can discover your insights by posing and addressing your questions.

Business Intelligence 52

Business Intelligence BI Data Mining Data Analysis 52

Data Science Blog: Data Engineering

NOVEMBER 15, 2023

The database for Process Mining is also establishing itself as an important hub for Data Science and AI applications, as process traces are very granular and informative about what is really going on in the business processes. This aspect can be applied well to Process Mining, hand in hand with BI and AI.

Architecture 52

Architecture Database-centric Process BI 52

Data Engineering Podcast

MARCH 20, 2022

How does it compare to systems such as Clickhouse (for OLAP) or CubeJS/GoodData (for embedded analytics)? How do the operational needs of a database engine change as you move from serving internal stakeholders to external end-users? What are the cases where Pinot is the preferred choice? Can you describe how Pinot is architected?

Datasets 100

Datasets Kafka Analytics Application SQL 100

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.

Kafka 52

Kafka Data Warehouse BI Analytics Application 52

Cloudera

FEBRUARY 8, 2024

This is similar to disabling indexes in databases for certain reasons. The support for Apache Iceberg as the table format in Cloudera Data Platform and the ability to create and use materialized views on top of such tables provides a powerful combination to build fast analytic applications on open data lake architectures.

Metadata 93

Metadata Data Warehouse BI AWS 93

Rockset

MARCH 31, 2022

On top of that, I had to make that data available to our custom-built application via a secure RESTful endpoint with a less than one second response time. By day three of my new job at Sounding Board, I was able to meet those requirements, build, and demonstrate a real-time, reporting and analytics application using Rockset and Retool.

MongoDB 52

MongoDB Data Architect Data Schemas SQL 52

Striim

AUGUST 31, 2023

Stream processors, storage layers, message brokers, and databases make up the basic components of this architecture. While they are well suited for near-real-time analytics applications, they may not be the best choice for batch processing jobs or those that require intensive computation or machine learning algorithms.

Data Integration 69

Data Integration Architecture Amazon Web Services ETL System 69

Rockset

FEBRUARY 24, 2023

Introduction Let’s get this out of the way at the beginning: understanding effective streaming data architectures is hard, and understanding how to make use of streaming data for analytics is really hard. Stream processing or an OLAP database? Kafka or Kinesis ? Open source or fully managed? Streaming data has been around for decades.

Kafka 52

Kafka AWS Amazon Web Services Programming Language 52

Rockset

MARCH 15, 2021

When working with a real-time analytics system you need your database to meet very specific requirements. 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.

MongoDB 40

MongoDB Data Ingestion Analytics Application Kafka 40

Cloudera

AUGUST 13, 2021

Whether it is consuming log files, sensor metrics, and other unstructured data, most enterprises manage and deliver data to the data lake and leverage various applications like ETL tools, search engines, and databases for analysis. What is the impact on the business?

Data Pipeline 109

Data Pipeline Data Lake ETL Tools Unstructured Data 109