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.

Troubleshooting cloud services and infrastructure is an ongoing challenge for organizations of all sizes. As organizations adopt more cloud services and their cloud environments grow more complex, they naturally produce more telemetry data – including application, system and security logs that document all types of events. All cloud services and infrastructure components generate their own, distinct logs.

Modern business requires a range of digital components to communicate effectively when transferring data and delivering critical messages. Application programming interfaces, or APIs, are sets of rules that regulate exactly how certain apps or machines connect. If you work with data at all, you’ll have heard of REST or RESTful, and REST APIs — but what is REST API design? We explain below.

According to Forbes , 95% of companies need to manage unstructured data and use it to gain actionable insights. Data processing is the way to do just that. Unfortunately, poor data management occurs when companies don't make full use of the information they collect.

Apache Ozone is a scalable distributed object store that can efficiently manage billions of small and large files. Ozone natively provides Amazon S3 and Hadoop Filesystem compatible endpoints in addition to its own native object store API endpoint and is designed to work seamlessly with enterprise scale data warehousing, machine learning and streaming workloads. The object store is readily available alongside HDFS in CDP (Cloudera Data Platform) Private Cloud Base 7.1.3+.

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.

The COVID-19 global pandemic has changed the ways we work, including how we use data, forever. Amidst the crisis, the analytics industry is experiencing its own paradigm shift.

During the process of turning data into insights, the most compelling data often comes with an added responsibility—the need to protect the people whose lives are caught up in that data. Plenty of data sets include sensitive information, and it’s the duty of every organization, down to each individual, to ensure that sensitive information is handled appropriately.

We rely on advanced data platforms that extract data from multiple sources, clean it, and save it so data scientists and analysts can gain insights from data. Data seems to flow seamlessly from one location to another, supporting our data-driven decision-making. The entire system runs smoothly because the engineering operations under the hood are correctly set and maintained.

COVID-19 vaccines were developed in record time. One of the main reasons for the accelerated development was the quick exchange of data between academia, healthcare institutions, government agencies, and nonprofit entities. “COVID research is a great example of where sharing data and having large quantities of data to analyze would be beneficial to us all,” said Renee Dvir, solutions engineering manager at Cloudera.