Building an entirely new data connector is difficult, especially when you’re already heavily swamped with monitoring and maintaining your existing custom data pipelines. When you have an ad-hoc Toggl to Redshift connection request from your HR and accounting teams, you’ll have to compromise your engineering bandwidth with this manual task. We understand you are pressed for time and require a quick solution. If you only need to download and submit a couple of CSV files, this should be a piece of cake. Alternatively, you might use an automated solution for the same.

Well, worry no further! We’ve prepared a simple and straightforward guide to help you replicate data from Toggl to Redshift. Leap forward and read the 2 simple methods.

How to Replicate Data From Toggl to Redshift?

To replicate data from Toggl to Redshift, you can do either of the following:

  • Use CSV files or 
  • A no-code automated solution. 

We’ll cover replication via CSV files next.

Replicate Data from Toggl to Redshift Using CSV Files

Follow along to replicate data from Toggl to Redshift in CSV format:

Step 1: Export CSV Files from Redshift

For Exporting Time Entries

  • Open the Toggltrack window.
  • Go to the left navigation pane, then in the ANALYZE section, click on the “Reports” option.
  • Select the reports you want to export.
  • Then, to the top-left corner of the screen, click on the download icon. Click on the “Download CSV” option.
Downloading reports from Toggl
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You can visit here for further information about downloading detailed reports from Toggl.

For Exporting User and Timeline Data

Users can download their profile data as well.

  • Visit the Profile Settings page.
  • Click on the “Export account data” button towards the top-right corner.
  • Now, check the items you want to export. Then click the “Compile file and send to email” button.
  • This file would be in a zip folder. Using a CSV file converter, you can extract and convert the data into CSV.

For Exporting Workspace Data

Only workspace admins have access to export workspace data. 

  • Go to the left navigation pane, then click on theSettingsoption.
  • Now, select the “Data export” tab. You can export projects, project members, tasks, clients, tags, user groups, clients, teams, subscription invoices, and more here.
Exporting Workspace data from Toggl
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  • After choosing the data you want to export, you can select the “Compile file and send to email” button.
  • Data will be exported in JSON format except for invoices in pdf format.
  • You can then convert all these files into CSV format using a CSV converter.

For Exporting Ingishts and Data Trends

  • Open the Toggltrack window.
  • Go to the left navigation pane, then in the ANALYZE section, click on the “Insights” option.
  • Then select the appropriate choice from the options available.
Exporting Insights from Toggl
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  • Then, to the top-left corner of the screen, click on the download icon. Click on the “Download CSV” option.

Step 2: Import CSV Files into Redshift

  • Create a manifest file that contains the CSV data to be loaded. Upload this to S3 and preferably gzip the files.
  • Once loaded onto S3, run the COPY command to pull the file from S3 and load it to the desired table. If you have used gzip, your code will be of the following structure:
COPY <schema-name>.<table-name> (<ordered-list-of-columns>) FROM '<manifest-file-s3-url>' 

CREDENTIALS'aws_access_key_id=<key>;aws_secret_access_key=<secret-key>' GZIP MANIFEST;
  • You also need to specify any column arrangements or row headers to be dismissed, as shown below:
COPY table_name (col1, col2, col3, col4)
FROM 's3://<your-bucket-name>/load/file_name.csv'
credentials 'aws_access_key_id=<Your-Access-Key-ID>;aws_secret_access_key=<Your-Secret-Access-Key>'

-- Ignore the first line
COPY table_name (col1, col2, col3, col4)
FROM 's3://<your-bucket-name>/load/file_name.csv'
credentials 'aws_access_key_id=<Your-Access-Key-ID>;aws_secret_access_key=<Your-Secret-Access-Key>'

This process will load your desired CSV datasets to Amazon Redshift in a pretty straightforward manner.

You will need to generate AWS Access and Secret Key to use the COPY command and complete the Toggl to Redshift data replication process.  

With the above 2-step approach, you can easily replicate data from Toggl to Redshift using CSV files and SQL queries. This method performs exceptionally well in the following scenarios:

  • Low-frequency Data Replication: This method is appropriate when your HR & accounting teams need the Toggl data only once in an extended period, i.e., monthly, quarterly, yearly, or just once. 
  • Limited Data Transformation Options: Manually transforming data in CSV files is difficult & time-consuming. Hence, it is ideal if the data in your spreadsheets is clean, standardized, and present in an analysis-ready form. 
  • Dedicated Personnel: If your organization has dedicated people who have to manually download and upload CSV files, then accomplishing this task is not much of a headache.
  • Low Volume Data: It can be a tedious task to repeatedly download & write SQL queries for uploading several CSV files. Moreover, merging these CSV files from multiple departments is time-consuming if you are trying to measure the business’s overall performance. Hence, this method is optimal for replicating only a few files.

When the frequency of replicating data from Toggl increases, this process becomes highly monotonous. It adds to your misery when you have to transform the raw data every single time. With the increase in data sources, you would have to spend a significant portion of your engineering bandwidth creating new data connectors. Just imagine — building custom connectors for each source, transforming & processing the data, tracking the data flow individually, and fixing issues. Doesn’t it sound exhausting?

Instead, you should be focussing on more productive tasks. Being relegated to the role of a ‘Big Data Plumber‘ that spends their time mostly repairing and creating the data pipeline might not be the best use of your time.’

To start reclaiming your valuable time, you can…

Replicate Data from Toggl to Redshift Using an Automated ETL Tool

An automated tool is an efficient and economical choice that takes away a massive chunk of repetitive work. 

To name a few benefits, you can check out the following:

  • It allows you to focus on core engineering objectives while your business teams can jump on to reporting without any delays or data dependency on you.
  • Your sales & support teams can effortlessly enrich, filter, aggregate, and segment raw Toggl data with just a few clicks.
  • The beginner-friendly UI saves the engineering team hours of productive time lost due to tedious data preparation tasks.
  • Without coding knowledge, your analysts can seamlessly create thorough reports for various business verticals to drive better decisions. 
  • Your business teams get to work with near-real-time data with no compromise on the accuracy & consistency of the analysis. 
  • You get all your analytics-ready data in one place. With this, you can quickly measure your business performance and deep dive into your Toggl data to explore new market opportunities.

As a hands-on example, you can check out how Hevo Data, a cloud-based No-code ETL/ELT Tool, makes the Toggl to Redshift data replication effortless in just 2 simple steps:

  • Step 1: To get started with replicating data from Toggl to Redshift, configure Toggl as a source by providing your Toggl credentials.
Configure Toggl Track as source for replicating data from Toggl to Redshift
Image Source
  • Step 2: Configure Redshift as your destination and provide your Redshift credentials.
Configure Redshift as destination for replicating data from Toggl to Redshift
Image Source

In a matter of minutes, you can complete this No-Code & automated approach of connecting Toggl to Redshift using Hevo Data and start analyzing your data.

Hevo Data’s fault-tolerant architecture ensures that the data is handled in a secure, consistent manner with zero data loss. It also enriches the data and transforms it into an analysis-ready form without writing a single line of code.

Hevo Data’s reliable data pipeline platform enables you to set up zero-code and zero-maintenance data pipelines that work efficiently. By employing Hevo Data to simplify your Toggl to Redshift data integration needs, you get to leverage its salient features:

  • Reliability at Scale: With Hevo Data, you get a world-class fault-tolerant architecture that scales with zero data loss and low latency. 
  • Monitoring and Observability: Monitor pipeline health with intuitive dashboards that reveal every state of the pipeline and data flow. Bring real-time visibility into your ELT with Alerts and Activity Logs. 
  • Stay in Total Control: When automation isn’t enough, Hevo Data offers flexibility – data ingestion modes, ingestion, and load frequency, JSON parsing, destination workbench, custom schema management, and much more – for you to have total control.    
  • Auto-Schema Management: Correcting improper schema after the data is loaded into your warehouse is challenging. Hevo Data automatically maps the source schema with the destination warehouse so that you don’t face the pain of schema errors.
  • 24×7 Customer Support: With Hevo Data, you get more than just a platform, you get a partner for your pipelines. Discover peace with round-the-clock “Live Chat” within the platform. Moreover, you get 24×7 support even during the 14-day full-feature free trial.
  • Transparent Pricing: Say goodbye to complex and hidden pricing models. Hevo Data’s Transparent Pricing brings complete visibility to your ELT spending. Choose a plan based on your business needs. Stay in control with spend alerts and configurable credit limits for unforeseen spikes in the data flow. 
Get started for Free with Hevo Data!

What Can You Achieve by Replicating Your Data from Toggl to Redshift?

Replicating data from Toggl to Redshift can help your data analysts get critical business insights. Does your use case make the list?

  • Clients from which geography do you serve the most?
  • Which project members work heavily in the US region?
  • What is the average daily variation of all the users?
  • Who are the significant contributors to a project?
  • How to optimize your employees’ workflow?

Summing It Up

Exporting and importing CSV files would be the smoothest process when your HR & accounting teams require data from Toggl only once in a while. But what if the HR & accounting teams request data from multiple sources at a high frequency? Would you carry on with this method of manually importing & exporting CSV files from every other source? In this situation, you would rather choose to liberate your manual jobs by going for a custom ETL solution.

However, a custom ETL solution becomes necessary for real-time data demands, such as monitoring daily activities across different platforms or viewing the division of billable working hours across divisions. You can free your engineering bandwidth from these repetitive & resource-intensive tasks by selecting Hevo Data’s 150+ plug-and-play integrations (including 40+ free sources such as Toggl).

Visit our Website to Explore Hevo Data

Saving countless hours of manual data cleaning & standardizing, Hevo Data’s pre-load data transformations get it done in minutes via a simple drag n-drop interface or your custom python scripts. No need to go to your data warehouse for post-load transformations. You can run complex SQL transformations from the comfort of Hevo Data’s interface and get your data in the final analysis-ready form. 

Want to take Hevo Data for a spin? Sign Up for a 14-day free trial and simplify your data integration process. Check out the pricing details to understand which plan fulfills all your business needs.

Share your experience of connecting Toggl to Redshift! Let us know in the comments section below!

Manisha Jena
Research Analyst, Hevo Data

Manisha Jena is a data analyst with over three years of experience in the data industry and is well-versed with advanced data tools such as Snowflake, Looker Studio, and Google BigQuery. She is an alumna of NIT Rourkela and excels in extracting critical insights from complex databases and enhancing data visualization through comprehensive dashboards. Manisha has authored over a hundred articles on diverse topics related to data engineering, and loves breaking down complex topics to help data practitioners solve their doubts related to data engineering.

No-code Data Pipeline for Amazon Redshift