Companies use predictive and business analytics to gain an advantage over their competitors and claim a bigger share of the market. But with the accelerated proliferation of data volume, speed and variety, establishing a system to make sense of this data is posing ever-increasing challenges. Several data solutions - from databases to data lakes - have emerged to empower companies of all sizes to take over their data and use it to accelerate growth.

Create an animated Keyword ranking report using your Search Console data to show performance over time in 90 seconds.

Revenue monitoring not only involves monitoring huge amounts of data in real-time but also finding correlations between thousands, if not millions, of customer experience and other metrics. Are traditional monitoring methods capable of detecting a correlation between a drop in user log-ins and a drop in revenue as it’s happening? For many reasons, the answer is no.

The Oil and Gas industry is arguably more familiar with managing an array of changing risk factors than almost any other sector in the United States. The industry is used to facing strong headwinds and has proven itself adept at adjusting to often rapidly shifting business conditions, whether that is regulatory change, big fluctuations in supply and demand, or evolving security supply chain concerns.

One of the big standouts for me in the recent environment is just how much of a shock COVID-19 has been for organizations. This is because many have become complacent about their data over the past decade and they’re now exposed. As Warren Buffet said, "Only when the tide goes out do you discover who's been swimming naked." To deal with the current economic situation everyone now has to lift the lid on their organization.

Since the very beginning, Unravel Data has made it a mission to ensure customers are successful, wherever they deploy their modern data platforms. On-premises, in the cloud, and in hybrid environments, Unravel supports the full stack of data processing engines to provide data operations visibility wherever it resides.

From dealing with security concerns to production monitoring, businesses need to analyze the log data of their systems to ensure everything is functioning normally. In a computing context, a log refers to automatically produced and time-stamped documentation of events related to a particular system. Analysis of log data helps businesses comply with regulations, security policies and audits, understand online consumer behavior, and comprehend system troubleshoots.

For many businesses, data has become the new currency. Organizations have come to rely on data insights to monitor the health of the business, track productivity, and identify key opportunities to optimize outcomes. However, implementing and maintaining analytics efforts can come with its own set of challenges. In order for organizations to make the most out of data, reliable data management is key. In this regard, many are turning to cloud-based analytics models for scalability.

Google Cloud’s enterprise data warehouse BigQuery offers some flexible pricing options so you can get the most out of your resources. Our recently added Flex Slots can save you money by switching your billing to flat-rate pricing for defined time windows to add maximum efficiency. Flex Slots lets you take advantage of flat-rate pricing when it’s most advantageous, rather than only using on-demand pricing.

BigQuery has several built-in features and capabilities to help you save on costs, manage spend, and get the most out of your data warehouse resources. In this blog, we’ll dive into Reservations, BigQuery’s platform for cost and workload management. In short, BigQuery Reservations enables you to: Quickly purchase and deploy BigQuery slots Assign slots to various parts of your organization

When you use data to guide your business decision-making process, you need to continually optimize your data analytics usage to get more out of that data. Here, we’ll share some ways to be more efficient with your BigQuery usage through ups and downs and changing demands.

This blog post series will put you in the mind of a defender. In cybersecurity, being a good defender means thinking like an attacker. Part 1 of this blog will focus on understanding why service accounts are excellent targets in the mind of the bad guys, and the threats and attacks a bad guy may use. In Part 2, we’ll lay out how to mitigate the threats and defend against these attacks using the tools Snowflake Cloud Data Platform gives you.

Making the digital shift has always been of key importance, but even more so in the last few months. As organizations across different verticals navigate a new landscape post-pandemic, it has become critical to reevaluate priorities and strategies for digital adoption. But enabling digital transformation requires a solid foundation, and cloud computing plays an integral role in this regard.

Classic data modeling and history-based actuarial models do not comprehensively work anymore. In order to get useful insights that can be implemented to support customers and the business, insurers must rapidly incorporate new data sources in their analysis. Current events that are different than anything we have seen in recent history force us to get used to a new world that cannot totally be evaluated and analyzed based on historical experience and knowledge.

Guest post by Mark Ferman, Sr. Oil & Gas Analytics Advisor Oil and Gas companies operate within one of the most demanding business environments on the planet with an array of complex challenges that regularly test their ability to innovate, plan, and execute strategic objectives.

This blog post is part of a series on Cloudera’s Operational Database (OpDB) in CDP. Each post goes into more details about new features and capabilities. Start from the beginning of the series with, Operational Database in CDP. This blog post gives you an overview of the NoSQL, component integration, and object store support capabilities of OpDB.

Here at Lenses.io, we’re focused on making data technologies such as Apache Kafka and Kubernetes as accessible to every organization as possible. It’s part of our DataOps vision and company DNA. Lenses is built by developers, for developers. We understand the headaches they live with and the challenges they face seemingly have to learn a new data technology every few months. We believe that’s just not the right model.

Editor’s note: Today we’re hearing from some of the team members involved in building BigQuery over the past decade, and even before. Our thanks go to Jeremy Condit, Dan Delorey, Sudhir Hasbe, Felipe Hoffa, Chad Jennings, Jing Jing Long, Mosha Pasumansky, Tino Tereshko, and William Vambenepe, and Alicia Williams. This month, Google’s cloud data warehouse BigQuery turns 10.

While cloud providers and data analytics firms are proliferating across markets and landscapes, what distinguishes one from another? How can you know which one holds the keys to your agency’s digital transformation? The reality is that no matter how slick the advertising, how pervasive the presence across conferences and webcasts, or how high the C-suite’s former government offices … it’s the offerings that matter most.

Many enterprise data science teams are using Cloudera’s machine learning platform for model exploration and training, including the creation of deep learning models using Tensorflow, PyTorch, and more. However, training a deep learning model is often a time-consuming process, thus GPU and distributed model training approaches are employed to accelerate the training speed.

We all know visualization alone is not enough in the world of modern BI. And, when Qlik Sense was introduced, we focused on building a world-class platform, driven by our associative engine, open APIs and modern architecture. Our vision was to drive all the major analytics use cases, and support a lightning fast pace of innovation for the next decade and beyond.

Time series data and real-time data acquisition is growing at a 50% faster rate than static, latent, or historical data. In some ways, it has become more important than any other type of data, as it provides real-time decision making, enables autonomous decisions at the edge, and allows for more complex Machine Learning (ML) applications. Time series data and real-time data acquisition dominate industrial use cases, as it is ubiquitous with the manufacturing process.

There are no silver bullets to solve your data issues in this Big Data world. This truism became repeatedly apparent in Searcher Seismic’s journey towards better data management. We realized that every choice has compromises associated with it, and a robust solution will necessarily integrate many individual pieces of technology and business processes. Having said that, there are some solutions that are undeniably better than others.

An exciting day today as Qlik launches the first-ever “History of the Fortune 500” as the official analytics partner of the Fortune 500. This unique data analytics site offers a window into the companies that have shaped America and the history that shaped them.

With COVID-19 now part of our daily lives, normal business operations and practices have been abandoned or curtailed and reinvented to sustain our businesses. Indeed, each department, division and team has had its own dynamics changed in this time of lockdown, and coping with process and workplace setting changes can present unique challenges.

Most business owners nowadays are not even aware if their website is reaching the potential customers or not. And believe us when we say this, not having an effective outreach is the same as not having a website. In today’s constantly evolving internet spectrum, if you own a website and intend to drive business through it, Search Engine Optimization (SEO) is imperative for you.

The importance of digital banking and electronic commerce has proven all the more important during the pandemic. Online shopping is the only choice in many cases for conducting commerce. A recent McKinsey report, pre-COVID 19 outbreak, revealed that retail digital banking acceptance was already high. It has increased to the point where 60% of customers under the age of 70 use digital channels. That number increases to 75% for those under the age of 50.

Bonus Material: PostgreSQL vs MySQL complete comparison table ‍ PostgreSQL (or Postgres) and MySQL are both relational database management systems (RDBMS for short). They are complex technological inventions designed to simplify your data operations across a wide variety of business use cases. The “relational” part of the name refers to the way in which they structure data as relations between rows and columns.

With the Oil and Gas Industry facing some unprecedented times and challenges with the price of crude oil, a slowing economy, and a forecasted decrease in the global market demand, there is a greater focus on a margin-based than production-based business. To address these constant challenges, new ways of thinking must be adopted to improve operational efficiency.

Apache HBase became a top-level project with Apache 10 years ago and Cloudera began contributing to it at the same time (2010). Over this time, it has become one of the largest and most popular open-source tools in big data and one of the most popular NoSQL databases.

May 14, 2020 — Allegro AI today announced that it joined the NVIDIA DGX-Ready Software program. Organizations that want to leverage AI to improve products and services often struggle to implement an advanced infrastructure that supports the unique and challenging demands of machine learning and deep learning.

People intuitively know that self-driving or autonomous cars present complex engineering challenges. Vehicle assembly is the easy part – we’ve been doing that for 100 years. The real challenge is a data challenge, acquiring and managing the data needed to run the vehicles’ brain, eyes, and ears. Autonomous driving technology complexity lies in the ability to ingest, store, analyze, and deploy large volumes of data & the high bandwidth needs of data-in-motion.

Across industries, the COVID-19 pandemic has made digital transformation an urgent necessity. With global calls to stay at home, businesses have gone digital, employees are working remotely, and consumers’ shopping preferences have shifted due to worries of disease transmission and the need for social distancing. In the retail world, this means catering to shifts in buying patterns, rethinking the distribution process, and transforming the sales pipeline as it is.

Today’s globalized organizations demand a new standard for communicating and sharing information. That includes data-rich content that moves through environments, networks, and locales. From being stored, analyzed, and shared, to quickly and effectively moving between environments, to spinning up in clusters and informing endless applications—data is more critical than ever.

This blog post is part of a series on Cloudera’s Operational Database (OpDB) in CDP. Each post goes into more details about new features and capabilities. Start from the beginning of the series with, Operational Database in CDP. This blog post gives you an overview of the languages, frameworks, and applications supported by Cloudera’s OpDB.

Data accessibility and analysis is a crucial part of getting value from your data. While there are many methods to view data when it comes to BigQuery, one common way is to export query results as an email on a scheduled basis. This lets end users get an email with a link to the most recent query results, and is a good solution for anyone looking for daily statistics on business processes, monthly summaries of website metrics, or weekly business reviews.

Manufacturing has historically been laggards in its adoption of emerging technologies as business processes, from the production line to back-office operations, have inherently been tied to legacy applications. But that is rapidly changing. Faced with competitive pressures, and driven by technological enhancements across broad sectors of the economy, today’s manufacturing leaders are seeking new ways to improve productivity, reduce downtime, and streamline operations and the supply chain.

Apache YuniKorn (Incubating) is a standalone resource scheduler that aims to bring advanced scheduling capabilities for Big Data workloads onto containerized platforms. Please read YuniKorn: a universal resources scheduler to learn about the rationale and architecture. Since the time of our last post, we are delighted to update that YuniKorn was accepted by the Apache incubator in Jan 2020!

It was three years ago, just after the Gartner Magic Quadrant (MQ) came out, that everything in customer success changed at Yellowfin. We had made it into the MQ again but we weren’t positioned where we believed we should be. We were a product-driven company that had been first to market for many of the functionalities that have since become expected in what BI vendors offer today.

While digging through data, Anna spots an interesting trend - some customers buy 3 times more than others. A segment of super-high spenders? This could make it rain for the company! She rushes to her boss, to show them the data, only to hear: “Yeah, I know. We have a bug, which inserts every order three times in the database. Were you not paying attention during our daily meeting?” Aw-kward.

It seems everyone is talking about machine learning (ML) these days — and ML’s use in products and services we consume everyday continues to be increasingly ubiquitous. But for many enterprise organizations, the promise of embedding ML models across the business and scaling use cases remains elusive. So what about ML makes it difficult for enterprises to adopt at scale?

Too often, companies are finding out after the fact that customers have stopped using their product or service, without enough notice to have done anything about it. The term customer churn is used to describe the loss of existing customers. These are people or organizations that were using a company’s products and/or services and have decided not to use them anymore, in favor of a competitor. Tracking customer churn is a key business metric for most companies.

Our Head of Product Design and Creative Director, Tony Prysten, has worked in brand, design and advertising roles over the course of his career. Bringing his wealth of experience to Yellowfin, he now shapes the creative and UX experience of our product. Here he shares his thoughts on how design flexibility improves the dashboard experience.

We are now living in a truly hyper-connected environment where vast amounts of data are being transferred, gathered, and consumed daily. There are 3.9 billion internet users globally – a number that is still growing. Just think about the last time you were waiting for a Zoom conference call to start.

With the announcement of the availability of Cloudera Data Platform (CDP), our customers have been buzzing with excitement. While each one of you has been trying out different aspects of CDP, we do recognize that you are in various stages of maturity in terms of your current product adoption or implementation. Particularly, our Cloudera DataFlow customers are in various stages of product adoption.

When speaking with customers, I often hear that they are committed to digital transformation and being a data-driven enterprise. Those may just seem like abstract, lofty words to aspire to but the reality is much more practical. We have major banks needing to ensure that they have a complete view of their customers, and can reduce churn through personalized service and offerings. Telecommunications giants that absolutely need to maintain network health so there are no dropped calls or missed messages.

For more than a decade, government CIOs have been gearing up for and championing digital transformation. And not a moment too soon: From federal headquarters to statehouses, agencies today are expected to mirror the near-seamless user experience of today’s commercial sector, delivering agile, efficient responsiveness to constituent needs.

Today we announced the launch of Qlik Alerting (formerly Ping Alerting from RoxAI), as a value-added product for Qlik Sense. Qlik Alerting provides sophisticated, data-driven alerts directly from Qlik Sense – empowering our customers to more proactively manage by exception and respond quickly when issues arise. Like the Jedi, everyone could benefit from having a sixth sense.

There’s no question that subscription-based businesses are an incredibly popular revenue model in today’s economy. While single transaction revenue models tend to fluctuate due to the seasonality of markets, subscription plans offer much more consistent and predictable revenues. Although the subscription revenue model can certainly be advantageous over one-off transactions, these businesses are also notoriously challenging to keep subscribers active on their plan.

The healthcare industry is crumbling under the weight of disruption. Newly empowered patients have high expectations for procedure and price transparency, and personal health information access, to enable informed treatment choices. Providers must deliver care faster, better and within a framework of rigorous quality, compliance, and cost containment guidelines. Drug and medical device makers are under pressure to deliver critical therapies quickly while ensuring safety, efficacy, and affordability.