The Kitchen Table
Explore the product knowledge we've built up together
This content, written by Corey Carruthers, was initially posted in Looker Blog on Dec 3, 2014. The content is subject to limited support.DonorsChoose.org is an online charity that makes it easy for anyone to help students in need. Teachers post their projects - it could be anything: classroom supplies, science kits, field trips, tablets - and citizen donors can decide which projects to support. Since launching in the early 2000s, DonorsChoose.org has funded over 212,000 teacher projects and given out over $280m. Learn how DonorsChoose.org is using Looker to secure funding and to invite principals, academics, and journalists to explore open datasets.
This content, written by Pedro Arellano, was initially posted in Looker Blog on Jun 4, 2019. The content is subject to limited support.The business intelligence (BI) landscape is quite different than when I began my career in the late ’90s. That was the age of centralized, IT-led projects, enterprise data warehouses, and on-premises deployments. Today we see decentralized, business-oriented environments, vast data lakes (and a number of “data swamps”), and a multitude of cloud-based solutions. This continuous evolution keeps my line of work fun and interesting. But it’s easy to lose perspective of just how much the BI and analytics industry has changed. , published last week by Dresner Advisory Services, is a helpful guide to track the evolution of the BI space. In this year’s edition of the study, Dresner identifies a number of unmistakable trends that reaffirm a shift in the way we’re used to thinking about BI. For example, the report shows that Executive Management and Operations ar
This content, written by Corey Carruthers, was initially posted in Looker Blog on Nov 6, 2014. The content is subject to limited support. Knewton is an adaptive learning infrastructure that powers educational products from many providers. Using predictive analytics, Knewton figures out the best way for individual students to learn and makes recommendations for what to learn next. Students are able to work at their own pace and on the materials that help them learn the subject matter best. With millions of students using Knewton, there is a lot of data to track. Using Looker, they have a set of tools that allows everyone in the company to see how they’re doing on a per-partner integration. Learn how Knewton is using Looker to create dashboards and visualizations, share data, and increase the number of projects their data team is able to manage.
This content, written by Colin Zima, was initially posted in Looker Blog on Oct 4, 2017. The content is subject to limited support.If you’re streaming fantasy football defenses -- selecting a new defense week-by-week -- finding the right defense to start can be difficult. While the projections are usually a decent starting point for picking a defense, I wanted to analyze data from the 2016 season to see if any additional insights or patterns could be gleaned, such as home vs. away games, time of the games and the day of the week the game is played. First, let’s take a quick look at the distribution of scoring for defensive fantasy points during the 2016 season: Looking at the cumulative probability and the number of games in which defenses earned a particular score, the data shows that about half of the time (specifically, 51.4%) you can expect to earn 6 points from your defense. Defenses are more likely to earn less than 6 points than they are to exceed it. 44.4% of the time defenses
This content, written by Lloyd Tabb, was initially posted in Looker Blog on Aug 21, 2013. The content is subject to limited support.“Miss Goldstein, please take a memo for me…. Colleagues, it has come to my attention that we are spending too much money on our secretarial staff, particularly as in the creation of memos. We’re going to need to limit the number of memos we can each send…” Can you imagine living back then? Having someone literally type up your (non-e)mail for you? My mother was a executive secretary. She was an amazing writer. But when she wrote, she spoke for someone else. Too many companies do the same today with engineers. A product manager dictates what should be built and engineers go code it with little input on what should be built or why it is being built. The product manager changes his mind frequently and whipsaws the engineers from one feature to another. At Looker we’re following a different path. Engineers and analysts interact directly with our customers and
What is pdt_build_failure_cleanup ?Knowledge Drop
Last tested: Jan 20, 2021 When a build fails or is detected as being canceled, we drop the table that may have been partially created. We do this to make sure the name is available for a subsequent build attempt. This content is subject to limited support.
This content, written by Scott Hoover, was initially posted in Looker Blog on Feb 25, 2014. The content is subject to limited support.The difference between big data and smart data comes down to size versus application. Big data is a buzz word for "lots of data." However, what one does with all of that data isn't entirely obvious from the term. Smart data, on the other hand, is what one does with their data—irrespective of size. Taking a smart-data approach, one might recognize that bigger isn't always better. For a predictive model, will a simple random sample suffice? What's the marginal impact on our model's accuracy when relying on 5 million rows versus 10 billion rows? Any worthwhile statistician will tell you that the marginal impact is negligible. Smart also means considering cost. While the hardware component of parallel computing solutions continues to go down, the time—and therefore the cost—associated with writing such a job using Hadoop can be considerable, particularly as
This content, written by Frank Bien, was initially posted in Looker Blog on Sep 27, 2017. The content is subject to limited support.Last year at JOIN, Looker’s annual data conference, I talked about the . The first wave started 30 years ago with monolithic stacks that were reliable but inflexible. You could only get answers to specific questions, but you could trust those answers. It was also the era of the data rich and the data poor, where those without access to data starved as they waited for someone to finally have time to help them. That frustration led to the second wave: a revolution toward self-service tools where users grabbed whatever data they could lay their hands on and threw it into data cleansing, blending, and visualization tools for analysis. But that revolution came at a cost. Scattered tools created a mess of silos that didn’t talk to each other, and you lost the ability to speak in a common language with anyone else at your company. Enter data chaos. Today, we’re
What does RendererNoCliprectFoundForElementError mean?Knowledge Drop
Last tested: Jun 24, 2019 The "nocliprect" error means that when Chromium polled the page for the size of the visualization element there was no visualization element present. Also worth pointing out that when we render individual dashboard tiles (AKA the Images of Visualizations option) that we convert each tile into it's own explore and capture the output from that. This error often comes up when there are no results in the rendered content.This error will appear as Uncaught (in promise) Error: Incompatible element passed to getClipRect in the logs. This content is subject to limited support.
This content, written by Jen Grant, was initially posted in Looker Blog on Mar 9, 2017. The content is subject to limited support.If you can prove what is working, what is not, how the mix works together and achieves your lead and revenue goals, then you will always have a seat at the proverbial “table.” And while we’ve all had a few point solutions that show us how that one single channel is working, it has been very difficult to pull all those solutions together to see the total picture. We’ve become Microsoft Excel jockeys pulling data into spreadsheets, connecting it together manually, and spending countless hours analyzing it to try to see the big picture. Or we’ve bought tools that say they do this for us, and only find out later that they pull the data, but they don’t connect it together for any broader insights. But today that all ends. This morning, Google announced their Google BigQuery Data Transfer Service that allow customers to pipe data from key Google apps - AdWords, Go
Last tested: Jan 21, 2019 In general, these are the steps:stop looker umount <shared-storage-dir> mount_nfs -o vers=4 nolock <shared-storage-dir> start lookerYou should probably make the changes in /etc/fstab so they're permanent. Then, when you go to remount, you can just do mount /lookershare to pick up the changes. This content is subject to limited support.
What is the custodian? (7.2+)Knowledge Drop
Last tested: Feb 4, 2020 The custodian in 7.2+ is meant to automatically find schedules that are stuck in a state that they cannot recover from and mark them as complete with an error message. It will not affect any schedules that are actually executing.The custodian runs as a background process every 5 minutes on all nodes and does two things:First, it checks all schedules that are marked as currently executing or delivering in the backend database along with the threads they're marked as running on and checks those threads to make sure those threads current state indicates it's working on that job. Second, it will check for the most recent jobs that started executing over an hour ago, and look for any jobs still in the queue waiting to execute that should have started before that one. If there are ones that are stuck in the queue, it will finalize those with an error message. This content is subject to limited support.
This content, written by Barbara Lawler, was initially posted in Looker Blog on Jan 28, 2020. The content is subject to limited support.As data speeds us forward into the future, is the smarter use of data our best hope for a more prosperous society and for healthier humans and the planet? What kinds of roles will humans have in that future? Are we our own best hope or the weakest link as more and more organizations “think” with data at machine speed? The entry into a new decade prompts us to ask the critical question about the role of expanded data collection and data creation, especially from observed data — in improved products, services, health treatments, urban solutions and in solving the world's economic and well-being problems. It seems that increasingly, businesses and governments are equally at odds and in partnership with each other. Driven by the growth of machine learning algorithms and the expansion of artificial intelligence programs in companies and in governments, some
This content, written by Jen Grant, was initially posted in Looker Blog on Jun 12, 2017. The content is subject to limited support. When we were kids, we were full of questions. And we weren’t afraid to ask “why?” to just about everything. As a mom of four, this “why” stage can be irritating at times, but I know my kids are asking because they want to learn. And as they learn more, they will make better decisions and have more interesting insights about the world around them. Believe it or not, within a business, the process is no different. Last year in New York we hosted our first user conference , bringing some of the most innovative minds in data together to collaborate, share ideas and connect over what data can make possible for business and even for the world. We were amazed with the variety of ways customers were using data to better understand their businesses. Buzzfeed’s data science team spoke on while Bonobos, Jet.com, and Casper discussed . All of these talks had one th
Will migrating from legacy --> K8s rebuild PDTs?Knowledge Drop
Last tested: Mar 2, 2021 No, the PDTs shouldn't regenerate. The instance slug that determines the reg key is now persisted in the internal DB for hosted customers for this reason, so when the DB is copied over the slug will be copied over too and the instance will keep using the same reg key. This content is subject to limited support.
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