Rupert Data

🎉 Meet Rupert: A game-changing analytics distribution platform that's revolutionizing the way businesses unlock value from their analytics! We've raised some money to grow and make Rupert available to even more teams.

Organization invest *a lot* in their analytics infrastructure – from pipelines to dashboards – but insights are idle and reactive so business stakeholders still don’t take enough data driven actions in their day-to-day to capitalize on the analytics investment.

In a dream world, each business user would have a dedicated analyst serving them curated insights—but that’s too costly and not scalable. With Rupert we’re delivering the next best thing.

Rupert reimagnes analytics distribution, closing the loop between analytics insights, next steps, and business outcomes. How?

Rupert is the only tool that deeply understands analytics products & business users’ consumption behavior. This lets us break down analytics into bite-size units & automate the delivery of timely personalized insights —with a suggested business action for each business user

With the right insight and a shortcut to the operational next step, users have a clear path to positive business impact. Customers like GoodRx, Solo Brands, Vida Health, and AppsFlyer love how Rupert simultaneously empowers the business to truly be data-driven and clears their analysts' plates.

The future of analytics in our organizations is proactively embedding actionable insights into business users’ workflows. Rupert is automating and bringing to reality this approach, allowing analysts full control and end-to-end visibility, so they can measure and boost the impact on their business.

To make this vision a reality, we've raised $8M led by Cortical Ventures and IA Ventures, with support from Citi Ventures, Joule Ventures, and founders/executives of generational data companies like Alation, Looker, Alteryx, SAP, Snowflake, Snowplow, Stitch, and Weights & Biases.

We're beyond excited to introduce Rupert to the world and bring its power to even more teams! Celebrate with us, learn more, and take Rupert for a spin (for free!) at www.hirupert.com! Join our team and help turn insights into value. 🚀

https://blog.hirupert.com/meet-rupert-delivering-business-outcomes-from-your-analytics/?utm_source=Facebook&utm_medium=Launch+Post

Meet Rupert: Delivering Business Outcomes from your Analytics Rupert is an analytics distribution platform that actually delivers business value from analytics. We are growing and want to make Rupert available for more teams. We raised some money to make it happen.

Excited to co-host this meetup with our partner AppsFlyer!

Their amazing analytics team Ziv Ben-Naim Ziv Peled Roi Hoffman & Daniel Zilberberg will share their work evolution towards personalized insights and how they actionize and distribute their analytics to their business stakeholders to deliver measurable business results.

To go deeper on the topic, we will also have a panel of some of Israel’s most forward-thinking data leaders — Maor Nativ, Eldad Gabay, Tali Fulman, Elizabet Noga, discussing their vision for actionability as well as a presentation by Talal Assir from Looker who will discuss how to set up the right infrastructure and culture for analytics actionability.

Link to sign up in the first comment!

Tipalti Fiverr Rapyd Simply - formerly JoyTunes

Dear Data Analysts, let's talk about your backlog.

If you’re a data analyst, you’re likely going to leave your job in the next year. You play a mission-critical role in your organization and are a versatile data expert who can analyze, code, and solve business problems.

And yet, you and your peers have one of the highest turnover rates, and it’s not surprising.

Analysts confront never-ending backlogs on a daily basis. As an analyst, you’re expected to communicate well with business partners, manage internal processes, and deliver quality products quickly (“we need this ASAP!”), all the while juggling various requests.

Moreover, the work is often repetitive and redundant since most of it has been done before by you or your teammates, but not saved in an accessible location. All of this makes the role highly demanding and results in a backlog that weighs heavily on your shoulders and your happiness.

These issues affect you and your company’s performance, and more importantly, agitate you in your day-to-day work. Frustrated by this reality, we identified the top challenges that cause this logistical nightmare:

Capturing and Managing Data Tasks:

Every morning, you probably open Trello to track personal tasks and platforms such as Monday.com, Asana, or Jira to collaborate with your team. Some requests also come in through Slack, email, or via a friendly ping on Google Hangouts. You likely deal with requests as they arrive or try to keep track of them on the fly (did anyone see a pen and paper?).

Adding more noise, stakeholders and business partners might also text, call, or drop by your desk with “quick questions” at any time. These haphazard interactions often make it difficult to ask proper questions that gather relevant context required to solve the problem.

Wide Variety of Tasks:

Throughout the day, some requests that fall on your plate are ad-hoc, which result in you creating one-off reports, tables, and analyses. Some are meta-questions about your work like “how-to’s” (“how do I filter in this report?”), while others may be repetitive debugging requests such as adjusting an SQL query to a recently updated schema. And if you’re lucky, you’re also managing more complex work that involves modeling and building pipelines.

Juggling these many types of tasks can naturally become confusing and requires a great amount of effort, especially when “simple” tasks become the most time-consuming.

Repetitive and Redundant:

During your weekly team meeting, you find out that a few months ago, Greg created a Looker view that is similar to what you've been working on tirelessly for the past few days. Meanwhile, Mary has already completed one of your requests on Snowflake but didn’t save it in an accessible path. It’s not the first time you find out that you’re doing redundant work. Can you guess how many tickets in your queue are almost identical to tasks that have been resolved in the past?

Too Many Tools:

After all that, you finally get down to work. You structure a SQL query for your current task in your favorite IDE and run it on your database or data warehouse. Alternatively, you write python code in Sublime, even though you’ve been told multiple times that you should switch to PyCharm.

To build your reports you need to pull and export data from BigQuery to Tableau, something that could take hours. You heard that a quick solution is to connect BigQuery to Google Data Studio or create a one-off Excel analysis, but this is harder to document and is easily forgotten. Did we mention your boss is thinking of switching to Power BI?

Lack of Data Discovery:

You finally finish the work itself. Ideally, it should become a valuable asset for your company. But in order for your time investment to have a strong return, it should be utilized in the future.

For that, you must make sure it’s easily accessible to you and your colleagues. How do you save, share, and obtain your assets today? Some analysts have a Google Doc with their most common work and SQL queries. Some use Github.
Others document them as status updates in a random project management tool, while the fortunate few use BI tools that have version control and cataloging.

We can only hope that the company’s assets are documented somewhere and that the owner hasn’t left the company yet, or else it’s all lost. Unfortunately, this situation is more common than not, leaving you to deal with more redundant work yet again.

So, how was your day?

By the end of it, you barely had time to look over the new data project you just received or to dive into that one problem you’ve been working on for over a month. The complexities, frustrations, and inefficiencies keep you from doing your best work - detracting from your time to think critically, dive deeper into analyses, and discover the best insights that help your team and business partners succeed.

With all of these roadblocks, it takes longer to deliver insights and answers to your business partners. As a result, they become exasperated from waiting and often take out their frustration on you, instead of recognizing the hard work.

Many companies have acknowledged this problem. Their solution? Hiring more analysts to lighten the workload, but that’s not scalable. Other companies try hacking together even more existing tools into the mix, but that doesn't address the root problem.

****

A Better Tomorrow

At Rupert, we imagine a different world. A world where analysts have proper support every step of the way. Our solution clears out the backlog that frustrates and blocks analysts from focusing on what matters most. It delivers data assets to analysts and their stakeholders when needed. It learns and automates work processes to eliminate redundancies, allowing analysts to push their companies forward, and makes work more enjoyable.

#4 Debugging

What are these tasks?

In short, debugging refers to troubleshooting problems. Like it or not, errors are inevitable and bugs will appear in your analyses, SQL, ETLs, and tools that you’re using. Debugging tasks can take a long time to solve– days, weeks, and sometimes (mainly with legacy systems) even months. You will recognize these tasks when you receive comments such as “These numbers don’t add up” or a panicked “I opened the dashboard and it’s all blank!”

How do we solve them?

The key is to address these tasks in an extremely organized manner. You’ll need to go back and review your work carefully to identify the errors and find exactly where they are located. The best place to start is at the bottom, and then work your way upstream until you discover what is causing the bug. Create a step-by-step process that you follow whenever a problem arises. Here is an example of how debugging a pipeline could look:

1. The BI Tool: Is it down? Are there any other reports that are dependent on the same underlying data, showing inconsistent numbers? Is the BI tool vendor reporting any issues? What about the data connectors to the downstream tables? Can you check them from the BI tool?

2. Downstream Tables: Are they slow to load? Do the numbers in them make sense? Use a test query or filter for each table to see if they’re producing the correct results. Document the test queries and their results.

3. Data Warehouse: Is it up and running? Are the transformation scripts that create underlying dependent tables working as expected? Check for column changes (name, data type, etc.), evil little devils.

4. ETL: Are the data source API connections throwing errors? Were there any scheduled jobs that failed to run?
Data Source: Did anything change with the data formatting or payload? Was there a modification in one of the columns? What about the credentials used to pull data from upstream sources? If the data is coming from a third-party tool, check to see if there are any reported issues.

While you’re going through the process, record the results and problems in one place. Since your data is interdependent, having all of the issues consolidated in one place will help you better pinpoint the root cause.

Then, timebox work for each bug based on severity to avoid going down rabbit holes for low-priority issues. After working methodically through the bugs, run the step-by-step process again to verify that no collateral damage was made.

Debugging is a team effort. If data engineers or developers are involved in the process, definitely work with a ticketing system or project management tool to manage the tasks efficiently. It’s also important to define who owns each step of the process within the data team.

With your business partners, communicate your findings regularly to reassure them that you’re taking care of the problem.

These strategies will help you solve your tasks more efficiently, but they can become cumbersome processes to manage. Without the proper support, the myriad of tasks you’re working on will become overwhelming and cause delays in your overall productivity. That’s why we created Rupert.

We would love to hear about your experiences with these tasks! Are there any other types that you spend a considerable amount of time on? How is your capacity divided among these tasks? Which types do you find to be the most challenging and why? Do you have any additional strategies for tackling them? Drop us a comment here or message us directly at [email protected].