One of the really interesting trends that I’m seeing in the marketplace relates to consultancies. Historically, the primary business model for consultancies was to sell their expertise and services. Every customer would get a unique service offering that was defined specifically for them.

Having spoken with many companies, I’ve learned that while they all monitor their application performance, infrastructure, product usage, conversion rates and a variety of other user experience parameters, very few monitor the actual transactions from their payment provider.

This article discusses four bottlenecks in BigData applications and introduces a number of tools, some of which are new, for identifying and removing them. These bottlenecks could occur in any framework but a particular emphasis will be given to Apache Spark and PySpark.

When Jackie Edwards wrote “Keep On Running” back in 1965, he certainly wasn't thinking about the future of computing. But, it's the Spencer Davis Group grooves that is the soundtrack playing in my head when I think about Kubernetes and the business value it brings. Enabling your environment to “Keep On Running” is just one of many of Kubernetes’ value adds.

Customer experience is a key factor in competitive differentiation in the digital economy. The online business model has changed, and today, the focus has shifted from brands to customers. It would not be an exaggeration to say that customer experience plays a central role in any business model.

The data science discipline has been around for quite some time now, but you may have noticed the field gaining traction in recent years. This is due to a number of factors: technology is rapidly developing, digital adoption is consistently increasing, and the amount of data available is growing in volume and complexity. All these and more have built a foundation that has made decision intelligence vital for organizations today.

Ongoing reports of the “Retail Apocalypse” were fueled once again in 2019 with more than a dozen well-known retail brands closing their doors forever. On the flip side, a “Retail Renaissance” is well underway – and signs indicate that retail leaders that have already invested in their digital transformation journey will continue to reap rewards well into the future.

Last week it was announced that Yellowfin jumped to Visionary in the Gartner 2020 Magic Quadrant for Analytics and BI Platforms. Toot toot! This is a massive achievement for the entire Yellowfin team putting us in the same room as products by the biggest players on the planet. What makes it so special is that we are a privately funded, Melbourne based organisation smashing it against huge, cashed-up tech giants.

Fresh off a new funding round which includes strategic cloud partner Microsoft, Databricks continues to make huge strides in its mission to ease Spark complexity and simplify analytics through its Unified Analytics Platform. Databricks has also graduated from “visionary” to “leader” in the latest Gartner Magic Quadrant for Data Science and Machine Learning Platforms in 2020.

We are excited to welcome the first release of 2020 which provides greater value through enhanced capabilities across our data analytics platform.

“If you can’t measure it, you can’t improve it” …this quote by Peter Drucker and the philosophy behind it is a key driving force behind modern management and the introduction of BI solutions to support the scaling and increased complexity of businesses. Analytics tools were developed to enable metric measurement and business monitoring across large scale, complex systems and to enable continuous improvements of business performance.

When a market grows as quickly as implantable medical devices, set to top a staggering $153.8 billion by 2026, the potential risk to patients can rise as well. As implantable medical devices proliferate, so do the number of costly, life-threatening, and reputation-tarnishing recalls. A single large recall can account for millions of device units.

We are continuing our blog series about implementing real-time log aggregation with the help of Flink. In the first part of the series we reviewed why it is important to gather and analyze logs from long-running distributed jobs in real-time. We also looked at a fairly simple solution for storing logs in Kafka using configurable appenders only. As a reminder let’s review our pipeline again

Last September, the revised Payment Services Directive 2 (PSD2) went into full effect, shifting open banking from futurism to a regulatory requirement for retail banks. But the EU is not alone in wanting to open up consumers’ financial data via APIs (application programming interfaces) to trusted Third Party Providers (TPPs). Neobanks and fintechs have been marrying technology and customer data as a market-grabbing strategy, thus increasing their competitive edge.

It’s recently been announced that we've made the Gartner Magic Quadrant for the seventh time. What’s most exciting is that this year we're in the visionary quadrant. This means that Yellowfin is now recognized for being an innovator in the BI space. We bring products to market that other people follow and that have something different to offer customers of BI software.

A pillar of 3rd-Generation BI, “Democratization of Data,” is the critical first step in maximizing the value of your BI solution. But, this means more than just simply opening up the information floodgates. That is not a formula for success. There are several important things to consider when democratizing data throughout your organization. I’ve outlined five of those key considerations below.

Themes make the entirety of WordPress. You can’t find a WordPress site without an instance of theming applied. The most popular theme of all time, Avada, has made over 12 Million dollars from selling at the initial price of $60! We’re not here to throw some internet facts on you for fun (although these are worth your time!). We looked around for the best & rare WordPress themes that boost your SEO, and make our Lord Google happy.

It is that time of year again. The much anticipated 2020 Gartner Magic Quadrant for Analytics and Business Intelligence Platforms has been published, and we are elated and humbled to announce that Yellowfin has been recognized as a “Visionary” in this year’s report. It’s our seventh consecutive year in the quadrant and just like last year, we believe we have made the most significant leap of any vendor in it.

Back in April last year, we made the business decision to make Keboola Connection available on Azure too (no, we're not quitting AWS). The story behind the decision is quite simple — our customers want it.

What is embedded analytics? Embedded analytics is the integration of analytical capabilities and data visualizations - real-time reports and dashboards - into another software application. This allows the end user to analyze the data held within the software application into which the analytics platform is embedded. With this analysis, the end user can identify and mitigate issues and spot opportunities to maximize.

Apache Hadoop Ozone was designed to address the scale limitation of HDFS with respect to small files and the total number of file system objects. On current data center hardware, HDFS has a limit of about 350 million files and 700 million file system objects. Ozone’s architecture addresses these limitations[4]. This article compares the performance of Ozone with HDFS, the de-facto big data file system.

Solving a problem programatically often involves grouping data items together so they can be conveniently operated on or copied as a single unit – the items are collected in a data structure. Many different data structures have been designed over the past decades, some store individual items like phone numbers, others store more complex objects like name/phone number pairs. Each has strengths and weaknesses and is more or less suitable for a specific use case.

Over the years, we’ve worked with a lot of software vendors who have embedded analytics into their product and there’s a range of reasons why they’ve chosen to do that. Some want to modernize existing analytics with a better solution, while others want to engage with more users or extend the use of their application to the C-Suite by delivering something of value to management like reporting.

In today’s age of technology, the processing of seismic data requires powerful computers, talented researchers, software, and skills. For the Oil and Gas Industry, its paramount to making strategic business decisions. Seismic data accurately helps to plan for wells, reduce the need for further exploration, and minimizes the impact on the environment.

Nowadays, we live in an attention economy. Everyday and every minute, people get a steady stream of notifications, message, and ads—all competing for attention. This barrage of information has raised the ever-important question: how do you break through the noise and get customers’ interest?

This blog discusses answers to questions like what is the right disk size in datanode and what is the right capacity for a datanode. A few of our customers have asked us about using dense storage nodes. It is certainly possible to use dense nodes for archival storage because IO bandwidth requirements are usually lower for cold data. However the decision to use denser nodes for hot data must be evaluated carefully as it can have an impact on the performance of the cluster.

Filtering is an underappreciated feature of business intelligence and analytics. Yet filters are critical to data analysis. Filters will probably be the primary method, of all the possible interaction types, that end users utilize. Welcome to part 3 of Yellowfin 9 Fresh Features. If you missed part 2, check out the enhancements to Yellowfin's automated data discovery - Signals. Yellowfin has a rich filter functionality that isn't available in some of the other leading analytics platforms.

A really interesting development I’ve seen in the data and analytic space lately is the rise of the data catalog. You may know these by another name such as a semantic or metadata layer, but they’re all fundamentally the same thing. Data catalogs aren’t new, they’ve been around for a long time. While some vendors like Yellowfin and Cognos have always had them, others like Tableau and Qlik are now just getting to them.

Over the course of my career in Financial Services, I have struggled with how few options I really had when it came to delivering the right information, to the right people, at the right time. It sounds sort of ridiculous considering how much time, money and effort the firms, for which I worked, spent on data warehouses, reporting systems, business intelligence tools and advanced analytics.

For public universities, metrics such as retention rate and graduation rate are important indicators for standing out in the competitive landscape. These success metrics are paramount to bringing in more students, making them successful, and continuing to grow a strong alumni network.

For Keboola, 2019 was a year of growing—and growing up. We evolved a lot, on both the business and product sides. In this blog, I want to give a quick overview of the changes, as well as give you some indication of what to expect from us in the next 6 months. Many of those improvements were inspired or directly driven by our users - there is a “wishlist” button available for everyone right in the Keboola Connection UI.