Analytics

For all of the buzz surrounding both artificial intelligence and data-driven management, many companies have seen mixed results in their quest to harness the value of enterprise data. To avoid those pitfalls, we mixed best-of-breed and proprietary solutions to develop our enterprise data platform (EDP), focusing much of our attention on a combination of smart changes in technology, culture and process for data lakes.

Like most organizations, Yellowfin has a CRM tool. The data in your CRM should be able to help you understand how you’re selling and how you win. But everyone I speak to is frustrated by the analytics they get from their CRM. We realized very quickly that the reporting in our CRM tool wasn't meeting our needs, so we built our own solution.

For data analysts, business intelligence professionals, and CTOs to optimize and scale business operations, they must first understand the business data that is available to them. One of the best platforms to turn complicated data points from multiple platforms into a singular, coherent data set is Microsoft Power BI. However, you must first prepare the data sets to eliminate fragmentations and create structural consistency. This article explores how to prepare data for Microsoft Power BI.

In my previous blog posts, I’ve talked about how you can aggregate data depending on the data type, as well as how you can re-express your data to get more value from it. For this post, let’s look at some of the different ways of measuring your data.

Running an eCommerce store is very much like flying a plane - you can reach unprecedented heights, but you won't be able to do it blindfolded. You have to see where you are going to touch the skies. E-commerce analytics gives you the guidance to make the right choice and scale your online store to new heights. In this article, we will take a deep dive into Shopify Analytics Shopify offers analytics as an out-of-the-box default service to all Shopify store owners and admins.

Hortonworks DataFlow (HDF) 3.5.2 was released at the end of 2020. The new releases will not continue under HDF as Cloudera brings the best and latest of Apache NiFi in the new Cloudera Flow Management (CFM) product. Getting the latest improvements and new features of NiFi is one of many reasons for you to move your legacy deployments of NiFi on this new platform. To that end, we released a few blog posts to help you migrate from HDF to CFM.

Ask any analyst how they spend the majority of their work day and they’ll tell you: Performing remedial tasks that provide no analytics value. 92% of data workers report that their time is being siphoned away performing operational tasks outside of their roles. Data teams waste an inordinate amount of time maintaining the delicate data-to-dashboards pipelines they’ve created, leaving only 50% of their time to actually analyze data.

Data paves the way for every strategic move made by banks and insurance companies. Whether looking to create a new service, complying with regulations, or overhauling and re-engineering legacy operations, a massive data project is always central to the effort. For financial services businesses, the pace at which they can reshape and repurpose data has become a key determinant of their ability to predict market trends and meet client expectations.

Heroku's Postgres open-source database is the most effective service for developers who want to build engaging apps. With all of its features and Heroku's experience managing databases, it guarantees security and compliance with GDPR.