While there has been some incremental improvements in the last few years, there has been nothing significant recently - and I think there are four clear reasons for that. Firstly, there has been a lot of consolidation in the industry recently. When that happens, behemoth vendors focus far more on selling than building new products that are going to disrupt the industry.

Cloudera Operational Database is an operational database-as-a-service that brings ease of use and flexibility to Apache HBase. Cloudera Operational Database enables developers to quickly build future-proof applications that are architected to handle data evolution. In the previous blog posts, we looked at application development concepts and how Cloudera Operational Database (COD) interacts with other CDP services.

Today, we are excited to announce the general availability (GA) of BigQuery materialized views. Materialized views (MV’s) are precomputed views that periodically cache results of a query to provide customers increased performance and efficiency.

Business analysts working with larger and larger data sets are finding traditional BI methods can't keep up with their need for speed. BigQuery BI Engine is designed to meet this need by accelerating the most popular dashboards and reports that connect to BigQuery. With the freshest data available, your analysts can identify trends faster, reduce risk, match the pace of customer demand, even improve operational efficiency in an ever-changing business climate.

Today’s enterprise data science teams have one of the most challenging, yet most important roles to play in your business’s ML strategy. In our current landscape, businesses that have adopted a successful ML strategy are outperforming their competitors by over 9%. The implications of ML on the future of business are clear. However, only 4% of enterprise executives today report seeing success from their ML investment.

Start-ups founded on analytics have been shaking up every industry. Finance has been disrupted by Monzo's data focus, Netflix’s analytics has upended film entertainment, and Swyfft has used data to change the game for US home insurance. Today's users have come to expect analytics in their applications.

Spreadsheets are everywhere! They are one of the most useful productivity tools available. They make organizing, calculating, and presenting data a breeze. Google Sheets is the spreadsheet application included in Google Workspace, which has over 2 billion users. Machine learning, or ML for short, has also become an essential business tool. Making predictions with data at low cost and high accuracy has transformed industries.

With a new year ahead, it’s time for financial services to pause, take stock of the “new normal,” and plan a path forward. COVID-19 forced nearly every industry to adapt to a new reality, and the financial services industry was no exception. Consumer habits shifted drastically. Suddenly, many people started working from home. Employee and customer needs changed. Adaptability was a necessity.

I’ve been a Business Intelligence (BI) analyst and evangelist for over two decades now. As you can imagine I’ve worked with many different BI platforms throughout my career, especially during my time as a BI Consultant. In this role, I was product agnostic, so from Power BI to Tableau, you name it, I used it! However, Qlik Sense quickly stood out to me as the most powerful and intuitive platform on the market.

I’ve met with lots of customers and prospects throughout my career. And, I’ve noticed that, when I’ve asked them to describe their current software situation, many would say the same things. “We should have updated this a long time ago.” “It’s embarrassing how long it takes to do a simple task.” “I bet other companies stopped doing things like this years ago.”