Data Academy 2022 Spring

Data Academy – launching my career as a Data Consultant

After a decade in my previous profession, I felt it was time for a change. I used to be a senior level expert, so making this kind of a change was exciting but also a bit terrifying. The Data Academy was ideal, because I felt it would better support my transition. After my studies, I applied to the Data Academy and I was accepted.

Our Data Academy group had future data platform engineers, future master data management engineers and me, the future visual data consultant. Everyone would learn a bit of each role, giving an introductory level to the topics. Solita’s internal experts held hybrid lessons, which meant real-life knowledge combined with expert tips. Regardless of your career path, the topics will be important to you at some point of your data career.

The best part of the Academy was the network that it offered to me. Firstly, I had my fellow academians. Secondly, I got a good look at all the departments and met colleagues. During the Academy, I met over 70 Solitans and got to know colleagues in different offices.

“The best part of the Academy was the network that it offered to me.”

Data Academy 2022 Spring

Growing as a specialist

After the Academy I dedicated my time to self-studies: Power BI and Azure certificates were my first targets, but I also continued my AWS studies, together with the Mimmit Koodaa community.

I will learn a lot through my work as well, because all the work projects are different in Solita. Most importantly, I can commit self-study time for my work weeks. I am participating in internal training, covering agile methods, Tableau, and service design. These courses will contribute my work in the future.

Solita community has warmly welcomed me. My colleagues are helpful, and they share their knowledge eagerly. I received work straight after the Academy, even quite demanding tasks, but there are always senior colleagues to turn to and discuss the matters.

Data Academy Spring 2022

Three tips how to become a Data Consultant

Check what my colleagues Johanna, Tuomas and Tero think of their work as a Data Consultant. The article gives you a good picture what our work is all about!

Learn one visualization tool well: it is a small hop to learn a second one later. Also, it is important to understand the licensing. Read my colleagues’ blog post about taking a deep dive into the world of Power BI. 

Of course, you need to understand the core fundamentals of data, and how you can utilize data in business. Here is a great example, how data creates value.

Finally, notable topics to learn are cloud technologies, databases and data modelling. They are strongly present in our every day work.

I could not be happier with my choice to join Solita via the Academy, and I sincerely recommend it!

The application to the Solita Data academy is now open!

Are you interested in attending Data academy? The application is now open, apply here!

A sad person looking at a messy table with crows foot prints. Birds flying away holding silverware.

Data Academians share 5 tips to improve data management

Is your data management like a messy dinner table, where birds took “data silverware” to their nests? More technically, is your data split to organizational silos and applications with uncontrolled connections all around? This causes many problems for operations and reporting in all companies. Better data management alone won’t solve the challenges, but it has a huge impact.

While the challenges may seem like a nightmare, beginning to tackle them is easier than you think. Let our Data Academians, Anttoni and Pauliina, share their experiences and learnings. Though they’ve only worked at Solita for a short time, they’ve already got a hang of data management.

What does data management mean?

Anttoni: Good data management means taking care of your organization’s know-how and distributing it to employees. Imagine your data and AI being almost as person, who can answer questions like “how is our sales doing?” and “what are the current market trends?”. You probably would like to have the answer in a language you understand and with terms that everyone is familiar with. Most importantly, you want the answer to be trustworthy. With proper data management, your data could be this person.

Pauliina: For me data management compares to taking care of your closet, with socks, shirts and jeans being your data. You have a designated spot for each clothing type in your closet and you know how to wash and care for them. Imagine you’re searching for that one nice shirt you wore last summer when it could be hidden under your jeans. Or better yet, lost in your spouse or children’s closet! And when you finally find the shirt, someone washed it so that it shrank two sizes – it’s ruined. The data you need is that shirt and with data management you make sure it’s located where it should be, and it’s been taken care of so that it’s useful.

How do challenges manifest?

Anttoni: Bad data management costs money and wastes valuable resources in businesses. As an example of a data quality related issue from my experience: if employees are maybe not allowed, but technically able, to enter poor data into a system, like CRM or WMS, they will most likely do that at some point. This leads to poor data quality, which causes operational and sometimes technical issues. The result is hours and hours of cleaning and interpretation work that the business could have avoided with a few technical fixes.

Pauliina: The most profound problem I’ve seen bad data management cause is the hindering of a data-driven culture. This happened in real life when presenters collected material for a company’s management meeting from different sources and calculated key KPI’s differently. Suddenly, the management team had three contradicting numbers for e.g. marketing and sales performance. Each one of them came from a different system and had different filtering and calculation applied. In conclusion, decision making was delayed because no-one trusted each other’s numbers. Additionally, I had to check and validate them all. This wouldn’t happen if the company properly manages data.

Person handing silverware back to another person with a bird standing on his shoulder. They are both smiling.

Bringing the data silverware from silos to one place and modelling and storing it appropriately will clean the dinner table. This contributes towards meeting the strategic challenges around data – though might not solve them fully. The following actions will move you towards a better data management and thus your goals.

How to improve your data management?

Pauliina & Anttoni:

  1. We could fill all five bullets with communication. Improving your company’s data management is a change in organization culture. The whole organization will need to commit to the change. Therefore, take enough time to explain why data management is important.
  2. Start with analyzing the current state of your data. Pick one or two areas that contribute to one or two of your company or department KPIs. After that, find out what data you have in your chosen area: what are the sources, what data is stored there, who creates, edits, and uses the data, how is it used in reporting, where, and by whom.
  3. Stop entering bad data. Uncontrolled data input is one of the biggest causes of poor data quality. Although you can instruct users on how they should enter data to the system, it would be smart to make it impossible to enter bad data. Also pay attention to who creates and edits the data – not everyone needs the rights to create and edit.
  4. Establish a single source of truth, SSOT. This is often a data platform solution, and your official reporting is built on top of it. In addition, have an owner for your solution even when it requires a new hire.
  5. Often you can name a department responsible for each of your source system’s data. Better yet, you can name a person from each department to own the data and be a link between the technical data people and department employees.

Pink circle with a crows foot inside it and hearts around. Next to it a happy person with an exited bird on his shoulder.

About the writers:

My name is Anttoni, and I am a Data Engineer/4th year Information and Knowledge Management student from Tampere, Finland. After Data Academy, I’ll be joining the MDM-team. I got interested in data when I saw how much trouble bad data management causes in businesses. Consequently, I gained a desire to fix those problems.

I’m Pauliina, MSc in Industrial Engineering and Management. I work at Solita as a Data Engineer. While I don’t have education in data, I’ve worked in data projects for a few years in SMB sector. Most of my work circled around building official reporting for the business.

 

The application to the Solita Data academy is now open!

Are you interested in attending Data academy? The application is now open, apply here!