data architecture framework
Articles Data Engineering Data Pipelines Data Structuring DataOps/Analytics Real time data

VIDEO: How Data Management capabilities fit together in an effective data architecture framework


A data architecture, in simple terms, is a framework for the IT infrastructure to be able to support the data strategy. It refers to the models, rules through which the data is collected, arranged, stored, transported, and utilized in an organization. Data capabilities include metadata management, master/reference data management, data

Real time Analytics
Analytics Tools Articles Case Studies Data Engineering Real time data

CASE STUDY: Effective use of data using the Real-time Analytics powered by Deloitte


Case: A wireless telecommunications company needed to leverage its vast volume of data more effectively for near real-time customer analytics. Challenge: The company was gathering sizeable volumes of data but was struggling to generate unique market insights. It faced a challenge with data latency, with an imposed reporting lag time of

Event-Driven Architectures on Apache Kafka
Articles Confluent Kafka Event Streaming Real time data Real time data streaming

VIDEO: Event-driven Architecture based on Apache Kafka – by Jay Kreps, CEO of Confluence


Apache Kafka has become one of the sought-after applications when one talks about real-time streaming. According to Jay Kreps, CEO of Confluence, it is one of the most popular open-source projects in the world. So what is it, and how is it suited in the current real-time-based Event-Driven Architectures on

Articles Case Studies Data Engineering Data Pipeline Event Streaming Real time data Real time data streaming Real Time Streaming

CASE STUDY: Alight Solutions accelerates digital deliveries with unified platform of streaming data pipelines


Company: Alight Solutions is a leading technology-enabled health, wealth, and human capital management solutions company in the US. The company is providing its services in over 100 countries across five continents and serves over 4,300 clients. Alight has recently taken initiatives to align its internal organization with the next-generation digital

Data processing in IoT
Articles Data Engineering Popular Real time data Real time data streaming Real Time Streaming Tutorials

VIDEO: Data streaming in IoT


The world around us is turning smart. We have smart watches, smart homes, smart buildings, smart cities, and even intelligent toasters. We have heaps of sensors and actuators throughout our homes rolling out to improve our experiences of living in the house. Where are we heading with this? We are

Rwal time data analytics using AWS Kinesis
Analytics Tools Articles Data Engineering DataOps/Analytics Event Streaming Real time data Real time data streaming Real Time Streaming Tutorials Videos

VIDEO: Why data streaming & Real-time data analytics became very popular recently?


Why is everyone these days talking about streaming analytics? Real-time data analytics has become one of the most valuable assets for any business. This is because the business community across all sectors now realizes that the new real-time insights are of greater value than those delayed by a few days

Data Pipelines and its types
Articles AWS Azure Data Engineering Data Pipeline Real time data

Types of Data Pipelines. When to use what?


A data pipeline is defined commonly as a set of bulk actions through which we extract data from a number of sources. This standardized, robotic process takes place when the system takes columns from different databases. They mould them with different columns with API as the target source. The combination

Data pipelines vs ETL pipelines
Articles Data Engineering Data Pipeline ETL Pipeline Real time data

ETL Pipeline vs Data Pipeline: An Overview


What Is an ETL Pipeline? Extract, Transform and Load, significantly known as ETL pipeline is a set of processes where you extract data from a particular source, and then transform it before you load it into the destination. The source can derive itself from anywhere, be it business systems or

Articles Case Studies Data Engineering Data Structuring Real time data Real time data streaming Real Time Streaming

CASE STUDY: PedidosYa used real-time data streaming to strengthen security


Delivery Hero-PedidosYa is a market-leading online food ordering platform in Latin America. It has an innovative web and mobile app providing its users access to 12,000 restaurants across six countries in the region. This case study explains how they used real-time data streaming to detect malicious & fraudulent activities &

Big Data Analytics at MoPub
Analytics Tools Articles Case Studies Data Pipelines Data Structuring DataOps/Analytics Real time data

CASE STUDY: MoPub Querying Terabytes of Data in Seconds using Big data analytics


MoPub provides monetization solutions for mobile app publishers and developers globally. The company platforms to drive maximum revenue for every ad impression and control the user experiences. It has over 1.7 billion monthly unique devices, 1 trillion ad requests, 52000 plus apps, and more than 180 demand-side partners on its

Big data analytics using Kafka
Analytics Tools Articles Case Studies Data Engineering DataOps/Analytics Real time data Videos

VIDEO: Big Data Analytics at Netflix


Netflix does not need any introduction. It has over 200 million subscribers. Last year Netflix users watched a collective hour of 6 billion per month. No surprise that the company is estimated to spend over $13 billion on content alone this year. All this means, Netflix has a mind-boggling amount of data that it

Euronext casestudy Apache Kafka Streams Examples
Articles Case Studies Confluent Kafka Event Streaming Kafka Kafka Architecture Kafka Streams Kafka Use Cases Real time data Real time data streaming

CASE STUDY: Pan-European Stock Exchange, Euronext using Confluent Kafka Streams for Trading Platform


Company: Headquartered in Amsterdam, Netherlands, Euronext is a leading stock exchange with a global reach. The Exchange operates in regulated securities and derivatives markets in Amsterdam, Brussels, Lisbon and Paris, Ireland, and the UK. In this case study, we will see Kafka Streams example on how Euronext used Confluent Kafka