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9 top trends that are driving AI and software investments

IT and data leaders are constantly challenged to keep up with new trends in emerging and disruptive technologies, and to determine how each can best aid the organization. In the midst of all the changes going on in 2019, it gets increasingly hard to know where to invest in all this new technology. To help add clarity, here are my thoughts on some of the most important trends that will shape data management and software development for the next couple of years.

How next-gen DI works

Data integration in the ‘Age of Digital’ brings in need for ETL development to happen at the ‘Speed of Business’ rather than at ‘IT Speed’. Data integration layer is the important ‘glue’ between the user engagement apps in the EDGE and the systems of record at the CORE of IT landscape. Application development for the Experience Layer happens at the ‘Speed of Business’ while changes in Integration Layer move at ‘IT Speed’.

Have you checked out Talend's 2019 summer release yet?

Have you had a chance to take a look at Talend’s summer 2019 product release? Our 2019 release has some exciting features that not only will help improve your productivity but will help you scale data projects across your organization. We are all about helping you do your work faster, and we think you’ll find the new features in this latest product release pretty great.

ELK with Talend cloud

ELK is the acronym for three open source projects where E stands for Elasticsearch, L stands for Logstash and K stands for Kibana. ELK is a robust solution for log management and data analysis. In this blog, I am going to show you how to configure ELK while working with Talend Cloud. The blog will focus on Loading Streaming Data into Amazon ES from Amazon S3.

5 best practices to deliver trust in your data project: Tip #4 Empower organizations with modern tools

Traditional tools for managing data integrity, such as data quality, governance and stewardship tools, were targeted at the most skilled data experts. With the advent of social networks, machine learning and smart pattern recognition technologies, these tools are getting simpler at every release. They now allow anyone with market or customer knowledge to contribute and collaborate in a data governance effort.

5 best practices to deliver trust in your data project: Tip #3 Take ownership around a single source of trusted data

Would you imagine e-commerce without an electronic catalog or the web without search engines? Digital transformation requires single points of access to enable a wider range of people to access a wider range of information.