Track all of your key business metrics from one screen
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Snowflake seamlessly converts large amounts of data into relevant information for your users and team anytime, anywhere.
Snowflake is a cloud-based data warehouse. It enables data storage, processing, and analytics solutions across multiple platforms. Snowflake combines a new SQL query engine with an innovative architecture designed for the cloud.
With Databox, you can create custom dashboards that users at all levels and with varying roles and expertise can use to make data-driven decisions. Databox allows you to combine metrics from multiple data sources and applications in a single dashboard, allowing you to transform your most important KPIs into meaningful insights that can be delivered to your desktop, mobile, Apple Watch, TV display, or Slack channels.
The Sessions metric in Hubspot measures the number of times a user interacts with a website within a specific period. It includes all page views, clicks, and other actions taken by the user during that time.
The New Contacts (w/o Offline Source) metric in Hubspot measures the number of new contacts acquired through online sources, such as website visits, social media, or email marketing campaigns, excluding any offline sources such as trade shows or direct mail.
New Leads metric in Hubspot refers to the total number of new contacts that have been added to the contacts database during a specific period of time, such as a day, week, or month.
New Contacts metric tracks how many new leads or contacts have been added to your Hubspot database within a specific time frame, often daily, weekly, or monthly.
New Visitor Sessions measures the number of unique users who visit your website for the first time within a specified time period.
Sessions by Source is a metric in Hubspot that shows the number of website sessions generated by different traffic sources, such as organic search, paid search, social media, email marketing, and direct traffic.
Emails Sent is a metric in HubSpot that tracks the total number of emails that have been sent from your account to your contacts or lists within a specific time period.
The New MQLs metric measures the number of new Marketing Qualified Leads generated within a specified time frame.
The New Contacts by Source metric shows the number of new contacts acquired from various sources within a defined period of time, helping businesses identify their most effective lead generation channels.
Emails Opened is a metric that reveals the percentage of recipients who opened your email. It's an essential measurement as it helps determine the success rate of your email marketing campaigns. It also enables you to identify the effectiveness of your email subject line and content.
The Emails Clicked metric measures the number of times recipients clicked on links within an email campaign, indicating engagement and interest.
New SQLs (Sales Qualified Leads) is a metric used to track the number of leads who have been identified as having a higher likelihood of becoming a customer and have been passed on to the sales team for follow-up in a given time period.
Blog views is a metric that tracks the number of times a blog post has been viewed by visitors on your website. It helps to measure the effectiveness of your content marketing efforts and the level of engagement with your audience.
New Customers (w/o Offline Source) is a Hubspot metric that shows the number of new customers gained through online channels, excluding any offline sources. It helps track the effectiveness of online marketing efforts and identify areas for improvement.
Contacts by Active List is a metric that measures the number of contacts who are currently on one or more active lists in HubSpot. It provides insight into the size of your audience and helps you keep track of how many contacts are engaged with your marketing efforts.
Landing Page Submissions metric measures the number of times visitors complete a form or register for an offer on a landing page, helping to measure lead generation effectiveness.
The Landing Page Views metric in Hubspot measures the number of times a specific landing page has been viewed by website visitors.
The Landing Page Views to Submission Rate metric measures the percentage of people who submit a form on a landing page after viewing it. It helps to evaluate the effectiveness of the landing page in converting visitors into potential leads.
The New Email Subscribers metric tracks the number of contacts who have recently subscribed to your email list. It helps measure the growth and success of your email marketing efforts.
New Leads by Source metric measures the total number of new leads generated from each source, allowing businesses to identify the most effective channels for lead generation and optimize their marketing efforts accordingly.
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LinkedIn Company pages dashboard template provides you with insights about followers growth, reach, engagement and more.
The Social Networks dashboard template integrates Facebook, Twitter, Linkedin and Instagram data. It shows daily traffic across the 4 networks and tracks follower counts..
Linkedin Demographics dashboard template looks at the followers on your company's Linkedin. It lets you know what industries and roles have enjoyed your marketing message.
Facebook Pages, Instagram Business, Linkedin Company Pages, Twitter overview
Social Media dashboard template shows activity across your 4 favorite social networks. It focuses on visitor and follower counts over various time periods.
Inbound Social Media Performance
This template is perfect for clients who want a general overview of their social media performance without getting into too much detail. This will summarize how their brand is doing within the social community.
This template moves you through the Attract stage by showing your social media follows and reach, blog view performance, and overall visibility trends.
Databox recommends to group data by day in the SQL query in Metric Builder. If you have several entries for the same date, you need to configure your SQL query to group all values for the given day. You can use Aggregation Functions such as SUM, MIN, MAX, AVG, Count in the SQL query and GROUP BY date DESC to take all values for a day into consideration and compute them based on used Aggregated Function to display all data from your SQL database.
You can learn more about Data Types in Databox here.
Databox has a 10,000-row count limitation for returned results of the Snowflake query. If the result order was not specified in the query, Databox can fetch all the data for 1 Dimension and no data for other Dimensions (since the available 10000 rows would be taken up by the history of the first Dimension).
To resolve this, the result order needs to be specified in the query, like the return order by date descending. Databox recommends adding the following clauses in the Snowflake queries if the result size is hitting the maximum row count limits:
ORDER BY DATE DESC
LIMIT 10000;
Once the return order is specified to display data in descending order on the date, the Dimensions (data results) should no longer be missing in Databox.
The error ‘<class ‘lib.SnowflakeController.InvalidArgumentException’>’ can occur while trying to connect the Snowflake Data Source in Databox if special characters are used in the Snowflake password. Databox advises users not to use special characters in the password as this may cause encoding issues during the connection of the Data Source.
Users need to check if the following characters are included in their Snowflake password and if so, replace them with other characters:
, ‘ ” / \ !? and spaces
More information on this is available in the help article here. This list of special characters is not final and Databox suggests trying to connect the Data Source with a password containing only ‘numbers’ and ‘letters’.
To resolve the error, the value column needs to be cast to double the numeric type. The assumption here is that Snowflake is returning decimal numbers as strings if they are not explicitly cast to a specific numeric type, which is why processing on the Databox end fails for such queries.
According to Snowflake’s documentation, DOUBLE, FLOAT, DOUBLE PRECISION, and REAL columns are displayed as FLOAT, but stored as DOUBLE. This is a known issue in Snowflake. You can read more about this here.
So if the error appears, the query should be updated following the info above (using CAST()), and then data should appear as expected without any errors in Databox.
The error ‘SQL compilation error: Object does not exist, or operation cannot be performed. Unable to connect to the server \”[name].snowflakecomputing.com\”. Check that the server is running and that you have access privileges to the requested database.’ can appear when opening a workbook with an existing Snowflake data connection.
The most frequent reason for the error is that the Snowflake user account does not have the necessary permissions – as a result, queries cannot be executed in Databox.
To resolve the error, ensure that your user account has permission to the server, warehouse, database, schema, and table in the connection.
More info is available here.