Topic "Data Engineering"
With the advent of high performing messaging systems like Apache Kafka, the adoption of enterprise messaging systems in enterprises is increasing exponentially. According to a recent survey, more than 90% of organizations are planning to use Apache Kafka in mission-critical use cases. According to Gartner, “Based on conversations with Gartner clients, we estimate that roughly... more
What is the Role of Big Data in Banking? Big data is defined by four main characteristics: volume, velocity, variety, and veracity. The global financial services industry generates massive amounts of structured and unstructured data every day by processing hundreds of billions of financial transactions as well as through interactions such as email, audio and... more
With the number of connected devices expected to reach 50 billion by 2020, there is a huge volume of data that is being generated. These devices are changing lives—and the nature of data. This data provides businesses with nearly real-time access into how its products are being used. Organizations need to identify and act on... more
Data is driving the strategic decisions within organizations. Because data is such an important asset, it is essential to capture data from a variety of sources across the enterprise, including partner ecosystem and third-party data. Many organizations have started initiatives to bring data from the various sources and move it onto data lakes or messaging... more
What is data engineering? Data engineering enables data users across the enterprise with clean, quality data they can trust, so they can drive better business insights and actions. Data engineering is the result of technology disruption in what we used to call big data. Overall, the industry is moving toward data management environments that deliver... more
Serverless is a cloud architecture that allows you to be free of managing servers, virtual machines (VMs), or containers. Serverless does not mean there are no servers involved (servers are still used for running applications). It simply means that you do not have to interact with or control the servers involved in the architecture. Serverless... more
This blog was co-authored by Nauman Fakhar, Director of ISV Solutions at Databricks. Apache Hadoop was born as an on-premises platform. Most of the use cases for early commercial Hadoop vendors focused on on-premises implementations of the open source data analytics platform. Eventually, Hadoop-as-a-Service—meaning Hadoop running in the cloud became increasingly popular. However, the Hadoop-as-a-Service... more