Digital transformation has been on the agenda for a long time, but the sudden need to respond to the unprecedented challenges of 2020, has meant the buzzword has become an executable reality for many enterprises. I recently came across a KPMG report that revealed that 80% of executives are increasing investments on emerging technologies now, to drive higher realized value in the future. Underlying digital transformation and investment decisions is a precious asset: data.

Recently, we took another look at our Chicago crime dataset to see what was different in crime as a result of the COVID-19 lockdown and what we found was fascinating. This is a dataset provided by the City of Chicago that tracks any type of reported crime. We often use it to demonstrate the power of Yellowfin. The first thing we saw was that a lot of crime went down. This chart shows crime rates in Chicago over the past two years.

In our last two posts, we talked with Deloitte’s Marc Beierschoder and Martin Mannion respectively about the requirement organizations have to deploy their data and analytics, quickly, into a hybrid environment. On top of that, there is the fundamental aspect of consistent security and governance of your enterprise data cloud and need for multiple users with different requirements to access data flexibly.

This blog post will present a simple “hello world” kind of example on how to get data that is stored in S3 indexed and served by an Apache Solr service hosted in a Data Discovery and Exploration cluster in CDP. For the curious: DDE is a pre-templeted Solr-optimized cluster deployment option in CDP, and recently released in tech preview. We will only cover AWS and S3 environments in this blog.

With the third generation of BI upon us, analytics solutions are leveraging AI to generate insights, automate tasks, and support new types of interactions. Qlik is consistently recognized as a leader in augmented analytics, and with the September 2020 release, we’ve set the bar even higher.

Communication Service Providers (CSPs) are in the middle of a data-driven transformation. The current scale and pace of change in the Telecommunications sector is being driven by the rapid evolution of new technologies like the Internet of Things (IoT), 5G, advanced data analytics, and edge computing. This is opening up new revenue opportunities, use cases, and even the possibility for different types of business models within the sector, changing the way that CSPs operate.

The pandemic has created monumental shifts in daily life, making all of us re-evaluate almost every aspect of our work and home lives.

In the final installment in the series, Vijay Raja, Director of Industry & Solutions Marketing at Cloudera shares his views on how the telecom sector is changing and where it goes next. Hi Vijay, thank you so much for joining us again. To continue where we left off, how are ML and IoT influencing the Telecom sector, and how is Cloudera supporting this industry evolution?

Companies from every industry vertical, including finance, retail, logistics, and others, all share a common horizontal analytics challenge: How do they best understand the market for their products? Solving this problem requires companies to conduct a detailed marketing, sales, and finance analysis to understand their place within the larger market. These analyses are designed to unlock insights in a company's data that can help businesses run more efficiently.

Google BigQuery was released to general availability in 2011 and has since been positioned as a unique analytics data warehousing service. Its serverless architecture allows it to operate at scale and speed to provide incredibly fast SQL analytics over large datasets. Since its inception, numerous features and improvements have been made to improve performance, security, reliability, and making it easier for users to discover insights.