I have a current report in Cognos that calculates sales made by contractors. Report gives the contractor names in rows while the columns have the sales they made that day (sales count, sales volume, net). This report is executed daily and exported as html. I am adding a YoY view also to this. Initially I had created a second table below the main one to show the YoY view but I want to have them in one table. When I try to combine them all into one list table it changes the data from previous year to current e.g moving sales count may 20 2023 right next to sales count may 20 2024 in the Cognos design view changes the count of the 2023 data to 2024. How can I avoid this?

What’s it like? Pros and cons? I have an interview there soon

Im an undergrad, looking to transition into business analytics. Do you recommend R or Python? I do have some background in Python basics. Please comment on it.

Hi, I am an international student looking to study MS in Business Analytics in the US. I did CS in my undergrad. Could you recommend some unis that are budget friendly yet the curriculum is really good. I am looking for a curriculum that is more of an MBA than AI or data mining if yk what I mean. Thank you in advance.

I was laid off last year and spent about three months actively applying for data analytics roles. During that time, I noticed a lot of news about layoffs and saw some of my friends go through similar challenges. Around January 2024, I decided to take a 9-month sabbatical to travel. I had always wanted to experience extended travel, and I knew a few people who did something similar after college. Considering the tough job market at the time, it felt like the right decision.

Now that the job market seems to be improving, I’m looking to transition back into analytics. Has anyone here navigated re-entering the field after a year-long break? How challenging was it? And is it advisable to be transparent about taking time off to travel when discussing the gap with potential employers?

I am working as a DA for 4+ yrs but I am not getting any good projects and even when they come it's very rare I get to work end to end. I want to switch into a senior role based on my experience. Since mainly I am getting involve in non-da work and whenever I get da it's not end to end which kin of is effecting my overall experience.

What skills would you suggest me to learn? Also as for my DSA it's like 5/10 and it's been long since I practiced.

These are my current skill sets: Tableau (not prep) SQL (not advanced like procedures or windows) Python (pandas mostly)

What should I be focusing on? Top 4 skills.

I’m graduating soon with a degree in Management Information Systems (MIS), and I’m trying to figure out what kinds of entry-level analytics roles would be a good fit for me. I really want to work in a role where I’m analyzing data and generating insights, but I’ll admit I’m not super confident in all areas of my skillset just yet.

Here’s the breakdown of where I stand:

I’m pretty confident when it comes to analyzing data and generating insights (especially from projects like analyzing Nielsen data). I enjoy spotting trends and presenting findings that make sense to others. I’m less confident in more technical areas like coding, working with JSON files, or statistics—I’ve worked on some projects involving these but feel like I still have a lot to learn. I’ve worked with tools like Excel, Python, Power BI, and Google Analytics, but I’d consider myself more of a beginner in Python and Power BI. Given that I’m looking for an entry-level role, I’d love some advice:

What kind of jobs should I target with my current skillset?

Are there job titles or industries that align with my strengths while giving me room to grow in technical areas?

What steps can I take to build confidence in coding and statistics?

Would certifications, specific projects, or courses help the most at this stage?

How do I position myself to stand out?

I’m worried my beginner-level technical skills might hold me back, so any tips on showcasing my strengths would be awesome.

Are there analytics roles that aren’t super coding-intensive?

I’d like to build a strong foundation in analyzing data before diving deeper into heavy coding roles.

I really want to find a role where I can start building my career in analytics while improving the skills I’m not as strong in yet. Eventually, I’d like to pivot into more technical roles, but for now, I’m looking for a good entry point.

Any advice or insights would mean a lot—especially if you’ve been in a similar place. Thanks in advance!

Hey Guys,
So I have an interview coming up for a food manufacturing company and they are going to give me a case study on Excel to work on. The job desc is focused on:
Recognize trends and patterns, utilizing large live and historical data,
Forecasting, Drawing hypothesis e.g. investigating sugar levels on a candy.

Does anyone here work in manufacturing (or better food manufacturing) and help give me an idea of what a typical dataset could look like?

I would love to start practising on some fake datasets, I asked ChatGPT but it isn't giving the most realistic datasets.

Any help us much appreciated!!

What did you study in college? And did it prepare you well for your current role as a DA?

Hi dear data analysts how did you get your remote job oppurtunity?

I'm currently a college student that is studying marketing analytics and I'm wondering where I can find internships for the summer. I'm honestly worried about finding one. I got invited to an interview where I record my answers but I completely bombed it and now I'm worried I won't be able to find anything. I seriously need help.

Hey all. In a professional environment working in Data Analytics, or as Business Analyst or in a related field how much is worth to learn R? Outside of Research & Academics there are advantage of learning and then using R over say Phyton. Phyton seems much more versatile and valuable and a requirement for many companies along with Excel, SQL + dashboarding.

We're on a project requiring to query multiple large dataset & multiple table using GPT to analyze the data (postgresql). Some of the tables have like 2,000 words text or more.

Any recommendations to tackle this issue?

I just watched Posthog's demo video and was mind blown. If you have used it in production, please share insights.

• It offers 8 different products, does it become confusing at some point? Is there a real advantage to having all those tools in one place?
• It seems to be feature rich, but do you see any major gaps compared with mixpanel/amplitude for analytics?
• How is the pricing compared to what you were using before?
• Any reasons why you wouldn't prefer such a tool over individual tools for analytics, experimentation, session replays etc?

It could apply to today or all time

Hello everybody,

I'm using Clarity for a few weeks now and wanted to download some heatmaps as PNG. Unfortunately everytime I download it it doesn't load the CSS and/or JavaScript. But in the application itself everything is fine.

Do I have to configure something that I miss?

I'm currently working in Workforce Analytics, and I've been wondering about the long term impact of specializing in a specific field of analytics. Would focusing too much on one domain like workforce or HR analytics make it harder to transition to another field, like business or financial analytics, later on?

Also, do hiring managers or HR professionals consider specialization a limitation when looking at candidates, or is the general skill set of an analyst data manipulation, visualization, etc. seen as transferable enough?

I’d love to hear your thoughts or experiences on this! Have you made a similar transition, or do you feel "boxed in" by your specialization?

Thanks

If you could automate one thing when working with your data, what would it be? Cleaning up messy data? Creating dashboards? Finding insights faster?

I lead a team helps operational efficiency. It’s come up once or twice about the ROI of my team.

My team obviously doesn’t bring the organization money as we aren’t the operations/sales folks.

But a lot of the reports and products we do end up saving time.

We just churned out a product that cut 100 hours of labor into seconds. I guess that’s an ROI.

Managers, how do you measure/define the worth of your teams?

Title says it all. What do you consider the most accurate measure for success when it comes to running a company's social media account? Would you prioritize engagement or sales?

I’m currently a UI developer at a very company, <20 employees in a niche industry. Since we’re small, a lot of employees wear a lot of hats. Outside of my dev work, my boss has occasionally tasked me with ad hoc analysis which usually entails running different SQL queries, creating basic reports in Excel or just automating things with PQ, and I’ve also created and maintained a few Tableau dashboards.

My issue is I’ve been at this company for 2 years and when I list out what I’ve done of my resume, it seems deceptive as I don’t *really* have 2 years of experience since I’m not doing DA work all the time, some weeks I’m only doing development tasks. I’ve only actually worked on 3 tableau dashboards, and most of my excel reports are basic pivot tables and calculations so I feel a bit deceptive.

I really do enjoy data analysis and the tasks I’ve done at work are what sparked that interest. I recently finished the google data analytics cert and I did a couple of Excel and Tableau projects voluntarily for some small business owners I know so I do possess some technical knowledge.

Am I overthinking this or is there a way I could spin my limited experience more transparently?

Following a spike in Direct traffic in GA4, I’ve been told by our cookie banner support that when a user refuses cookies or makes no choice in Consent Mode, this traffic falls into the Direct channel.

Has anyone ever truly experienced this?

I’m somewhat doubtful about that as I always thought sessions were not processed when a user refuses cookies (except through modeling, which is not active in the property anyway).

Please note that navigation is blocked prior to consent and the page is not reloading on consent.

1. Who is your target audience?
2. What data sources will your platform support?
3. How will you ensure data accuracy and consistency?
4. What kind of analytics (descriptive, predictive, prescriptive) will it offer?
5. How will it balance ease of use with advanced features?
6. What’s your plan for scalability, security, and compliance?
7. Will the platform include automation or workflow integration features?

Hi everyone,

I’m graduating next May and looking to start a career in Business Analytics. Would you recommend the Tableau Desktop Certification? Has it helped you professionally?

I appreciate your time and insights!

Hi, Can anyone let me know if this is normal for an entry level new grad data analyst role?

For context, I joined a new grad rotational program and I feel like I’m being over worked and also doing a lot more product/management work than data work.

I’m on a team of all product/non technical people and I’m the only data analyst/technical person on my team. Because of that I’m in charge of developing dashboards for my team, as well as requirements from cross functional teams. Getting data from different teams takes weeks of communication and negotiation, often escalating to their supervisor and it puts me in a really awkward position since, as a new grad, I feel uncomfortable demanding/requesting said confidential data from different teams . Since I’ve started I’ve designed and am now maintaining 4 different dashboards. My boss wants me to start writing requirement docs and also leading product meetings with different teams.

I guess I thought that being in a new grad entry role position, I would have a mentor to gain data analyst/bi skills but instead I feel like I’m overwhelmed with responsibilities and since it’s my first time doing bi and there isn’t a mentor/another data analyst on my team to bounce off of ideas and get help etc . there’s also an added learning curve with bi tools and cloud data management, which is hard to learn while also having to keep up with deadlines.

I don’t mean for this to come off as complaining, I’m super grateful to have a job and have people that trust me to develop these reporting tools, but I’m wondering if this is normal

Since graduating college, I've been searching for a DA job for a year and half. I've learned R through college. Learned SQL, Tableau, and a little bit of Python and Power BI. Even got a certification in Google Data Analytics. I settled for a accounting job and eventually went up to Pricebook Analyst (current job). Since my current employer has changed a lot, I've been seriously been getting back into learning programming again and seeking a Analytics role. Problem is: It's way harder now than it was a couple years ago.

Hey everyone!

Being direct:
Data Engineer with 10y experience, trying to do a move to Data Governance side. I want to be part of the DG Team, somehow in the future. Ideally I'll be a CDO.

I've got three proposal in hands:
(1)
1x for a Data Quality Analyst role, working very close to the Data Governance Team.
Business: bank industry
Tasks:
Maintain DQ
possibilities to evolve the DG framework, but it's not the focus. but I'll work close to the team.
Work with MS Purview
Work as a team in a "agile" methodology
Concerns: business limited scope, since I'll be QAing data for reports.
Pros: I'll work exactly on the field I want

(2)
2x for Data Architecture
Both companies (Industry Innovation and Telecom)
Both are trying to follow a Data Mesh Architecture.
Both don't have a strict DG framework implemented ; I'll have contributions to it, but will not implement it directly.
Don't know exactly which tools I'll work with.
Both don't work in agile methodology, since I'll work "alone", defining something and not necessarily build projects.
Concerns: tasks are not directly related with DG tasks.
Pros: Strategic position. Possibility to work with DG. Working on a Data Mesh centric idea, possibly designing data products (oh sh*, developing data products without a DG framework already implemented)

What brings me here:
How the f* do why choose? I really need to decide. All the three came to me on linkedin, are good companies with good salaries. Bank industry is in general more "close", no big progress, I think. But it's DG. However working as a Data Architect I'll be more strategically positioned to help on DG tasks, I believe.
Bank pays a little less.
All have good facilities and perks.
The thing here is essentially the tasks.

Any Data Architects/Data Quality/Governance Analysts here?

Thanks for your inputs!

I’m a final-year industrial engineering student, and I’ve recently started learning Power BI, Tableau, and Excel. I’ve been enjoying the field of analytics so far, but here’s the thing—I absolutely dislike coding. Even for VBA in Excel, I rely on ChatGPT to write the code for me. Luckily, my professor thinks it’s okay to use tools like that, so it hasn’t been an issue.

I’m curious to know more about the nature of work in analytics roles, such as Business Intelligence (BI) or Business Analysis. What does a typical day look like? Are these roles heavily reliant on coding, or can they be more focused on tools and insights?