We get a lot of questions from users who want to use Chartio to push their data harder. For those people, we're introducing Data Boot Camp, a introduction to data analysis using Chartio.
Today, Chartio is announcing Data Stores, a better way to store and transform data. We've always been at the forefront of agile business intelligence, and Data Stores makes Chartio even more agile.
We asked ourselves, 'What's the best way to measure how happy your customers are?' and investigated what other companies are doing. After some investigation, we settled on using a Net Promoter Score to measure customer satisfaction and explored more on NPS best practices.
Even after you've decided that you need a business intelligence system, it's easy to get lost in questions about data storage. How is my data stored, and how should it be? What kind of data storage does my business intelligence tool need? What's a data warehouse? Do I need one? If so, what kind of data warehouse do I need?
How happy are your customers? What can you do to make them happier? It's harder to answer those simple questions than you might expect. We recently decided to survey our happiest and least happy customers to find out how to improve Chartio and monitor our progress.
This blog post covers some common comparison operators in SQL and how to use them with the WHERE clause.
Chartio recently had the opportunity to analyze the data of Watsi, an innovative nonprofit based in San Francisco. And what we learned changed the way we thought about the economics of charity.
To combine tables you will have to JOIN them. This tutorial walks you through the steps to create a JOIN in SQL. In this example, we will answer the question - which customers have made the most purchases?
Our users love the Chartio dashboards they've been creating and sharing with their teams, and they've been looking for a way to give their customers access to a view of their data using Chartio. Today, we're announcing embedding - Chartio's solution for sharing data outside your company.
Chartio has added a bucketing step in the Data Pipeline, which divides the values from a column into a series of ranges, and then counts how many values fall within each range. You can use this step to create a histogram, which can be helpful in visualizing the distribution of data.
Amazon Redshift is commonly classified as a MPP (Massively Parallel Processing) or a shared nothing system. Aside from the single-node deployment option, an Amazon Redshift cluster is made up of a leader node and a number of compute nodes.
If you're a Chartio user, you already know that we make it easy to analyze and visualize your SQL data without touching SQL. Now, thanks to our new connection to Segment SQL, you can also work with customer event data from your applications, websites, and marketing.
The more queries you run on Amazon Redshift, the slower it will perform. Amazon Redshift Workload Management will let you define queues, which are a list of queries waiting to run. You can specify how many queries from a queue can be running at the same time (the default number of concurrently running queries is five).
New releases include a fixed dashboard title bar, hidden variables, new input widget, and dashboard variables in query mode.
Chartio gives you a lot of leverage over large databases stored in Amazon Redshift. But because you're executing complex queries against extremely large datasets - planning ahead will yield big benefits in both performance and cost.
If you're exporting PDFs from your Chartio dashboards -- or from individual charts -- you'll find our PDFs are now better-looking and more reliable.
Chartio's CSV import tool was already easy to use, but we've made some improvements to help you finish your imports faster and get started with your analysis sooner.
Even one inefficient query can cause performance issues, so the overall performance of your database can be greatly improved by examining your most expensive or most-used queries.
The engineering team is happy to announce that you can now create your own custom dashboard themes. In an effort to continue giving you control, we have added a theme editor so you can create a theme that suits your company colors or simply your personal preferences.
New releases include improved global filters, a new step to the data pipeline, arranging charts, and a shortcut to running queries.