Data Mesh, Data Stack, and the Holy Grail
If an organization is to be productive, it needs to work with the right data at the right times exactly where it needs them, across the whole structure and in each of its departments.
Systems | Development | Analytics | API | Testing
Modern Software Development For Today's Systems & Applications
Estée Lauder: Transforming the retail experience during a pandemic
Change is something every business leader has to deal with. But in the past two years, doing business has just gotten weird and harder. In this video, Christal Bemont, Talend's CEO and David Malloy, Executive Director of the Estee Lauder Companies discuss how he used healthy data to fuel a dramatic business transformation of the major cosmetics retailer.
Data In Motion: NASA and Aurica
Some 300 million years ago, Earth had one continent called Pangea. Over millions of years, that vast single land mass broke up and drifted in different directions, creating the seven continents that exist today. Since the planet changed so dramatically over millennia, it raises an obvious question: How will it change in the future? The same forces, plate tectonics and continental drift, that broke up Pangea hundreds of millions of years ago still exert themselves.
5 Secrets to Understanding Value Shoppers
Our five key points: Value shoppers are the savvy buyers, the ones always on the lookout for the best deals and who knows where to find every discount and coupon. If you're an e-commerce retailer, the importance of understanding your value shoppers can’t be overstated. Consumers searching for a great deal will absolutely look elsewhere if they’re not impressed by your online offerings.
Automate the Creation of Data Streams
Qlik Data Integration automates the creation of data streams and efficiently moves it to applications, data warehouses and data lakes, delivering business-ready data to Qlik Sense or other analytics solutions. This video includes an interview with Qlik's Adam Mayer, along with an extensive demo of Qlik's Data Integration solutions.
Modernizing the Analytics Data Pipeline
Enterprises run on a steady flow of best-fit data analytics. Robust processes ensure these assets are always accurate, relevant, and fit for purpose. Increasingly, organizations are implementing these processes within structured development and operationalization “pipelines.” Typically, analytics data pipelines include data engineering functions such as extract-transform-load (ETL) and data science processes such as machine-learning model development.
How to Improve Your Reporting Process: The Do's and Don'ts
What can you do to improve your reporting process? Learn what tactics to try and avoid from 59 data experts.
Commerzbank | Unleashing Hidden Data Treasures for Customers
Like many financial institutions, Commerzbank was challenged with staying flexible to meet customer needs, while also meeting regulatory compliance. In this Movers & Makers, Justyna Lebedyk, Product Owner in Big Data for Commerzbank, talks about how their digital transformation with the hybrid cloud and Cloudera allowed them to overcome this challenge.
Building and Managing the Modern Datastore: The Data Lakehouse
The 'data lakehouse' is quickly becoming popular in the data analytics community. Data lakehouse architecture combines the benefits of a data warehouse and a data lake. It aims to merge the data warehouse’s data structure and management features along with the flexibility and relatively low cost of the data lake. Watch this panel discussion to learn how the data lakehouse can address the limitations of the data lake and data warehouse architecture to deliver significant value for organizations. Explore why the data lakehouse is an ideal option for enterprise data storage initiatives.
MongoDB vs. PostgreSQL: Detailed Comparison of Database Structures
One of the most important parts of the function of any company is a secure database. With phishing attacks, malware, and other threats on the rise, it is essential that you make the right choice in order to keep your data safe and process it effectively. However, it can be extremely difficult to choose among the wide variety of database solutions on the market today. Two commonly-used options are Mongodb and Postgresql. What do you need to know about MongoDB vs. PostgreSQL?