Frontline healthcare providers don’t always have access to the latest and greatest technology. But when they are trying to fight a global pandemic with pen-and-paper tracking systems, something has to change. Dimagi is a tech company on a mission: to deliver scalable digital solutions for organizations to amplify their frontline impact.
The more an enterprise wants to know about itself and its business prospects, the more data it needs to collect and analyze. Additionally, the more data it collects and stores, the better its ability to know customers, to find new ones, and to provide more of what they want to buy. Sounds simple, but a surprising majority of U.S.
While many businesses struggled to keep pace with the changing economics of a global pandemic, the real estate industry was booming. The housing market reached record-breaking heights last month, with median existing-price homes rising 17.2% over the prior year. This increase in the average cost of a house was compounded by accelerated closing times, as the average house sold in 18 days, a record low.
Cloudera and Accenture demonstrate strength in their relationship with an accelerator called the Smart Data Transition Toolkit for migration of legacy data warehouses into Cloudera Data Platform.
The era of manual data management and governance is rapidly coming to a close. The size of the trove of data at nearly every company has become so enormous that it cannot be maintained using manual cleaning, cataloging, governance and search methods. The release of Lumada Data Catalog 6.1 breaks new ground in automating data management, cleaning and governance processes, making it easier to find data and grant access to those who need it.
In the final episode of season two of The Data Chief podcast, we talk with authors of four must-read books for data and analytics leaders — two new and two time-tested. As you invest in your continuous learning, here is the full round up of the latest top books I recommend for today’s data and analytics leaders.
French multinational automotive manufacturer Renault Group has been investing in Industry 4.0 since the early days. A primary objective of this transformation has been to leverage manufacturing and industrial equipment data through a robust and scalable platform. Renault designed an industrial data acquisition layer and connected it to Google Cloud, using optimized big data products and services that together form Renault's Industrial Data Platform.
Last week, we shared information on BigQuery APIs and how to use them, along with another blog on workload management best practices. This blog focuses on effectively monitoring BigQuery usage and related metrics to operationalize workload management we discussed so far.
In our modern world, accelerating the process of extracting insights from data is a complex challenge. Exacerbating this task are colossal data volumes, the expansion and use of multiple cloud platforms, and the increasing demands for self-service in a way that maintains compliance. Enterprises attempting to tackle the problem encounter various forms of friction everywhere they turn.
