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Pinned Threads
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4
shweta
Alex
janhavi
pangaeaX
- 3 months ago
Resources to Learn Data Science
A collection of the best courses, books, and tools to learn data science.
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5
- 7 months ago
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4
- 5 months ago
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3
- 7 months ago
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3
- 7 months ago
Weekly Posting Rituals
What are the key benefits of staff outsourcing
Staff outsourcing can offer numerous advantages to small businesses, particularly in terms of efficiency and cost-effectiveness. Here are some key benefits: Cost Savings: Staff Outsourcing allows businesses to avoid the…
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2
kashaf
- 3 months ago
What benefits come with employing a developer for Power BI?
Hire Power BI developer with cross-functional knowledge has several benefits, one of which is a deeper comprehension of various business processes and their interconnections. These developers are able to produce…
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4
KnowledgeKingX
- 1 year ago
How do data visualization consulting companies ensure the scalability of solutions?
Data visualization consulting company ensures scalability by designing solutions that can grow with the business. They implement data models and structures that can handle increasing data volumes without compromising performance.…
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4
- 7 months ago
Bounty Questions
🏅 Bounty: 200 pts
How often you update feature engineering after deployment to handle data drift in ML ?
In your machine learning projects, once a model is deployed, how often do you revisit and adjust the feature engineering process to address issues caused by data drift?What indicators or…
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4
- 3 months ago
🏅 Bounty: 200 pts
How much statistics you need to know as a data analyst?
I am planning to learn data analytics and i got overwhelmed by all the information at the internet so I am asking here how much statistics do you need and…
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2
- 3 months ago
What breaks when a deep learning model goes live?
Deep learning models often look reliable in training and validation, but real-world deployment exposes weaknesses that weren’t visible in controlled environments. Live data is messier, distributions shift, and edge cases appear more frequently than expected. These issues don’t always cause…
Has AI become part of your daily work or is it still mostly talk?
I keep hearing teams talk about being “AI-powered,” but in practice it often feels uneven. Some people use AI constantly for decisions, analysis, or automation, while others barely touch it or don’t trust the outputs enough to act on them.…
Is it timing delivering insight at the exact moment of choice?
Most organizations don’t struggle with a lack of data. They struggle with data that arrives after decisions have already begun to solidify. Insights are often technically sound, carefully analyzed, and clearly visualized, yet they surface only once meetings are over,…
At what point did you realize your BI setup was answering the wrong questions?
Most BI systems start with good intent: track performance, improve visibility, support decisions. But over time, dashboards often grow around what’s easy to measure rather than what actually matters. Teams keep adding metrics, leadership reviews charts every week, yet critical…
When was the last time a BI insight actually changed a decision you were about to make?
A lot of BI work ends at “visibility” dashboards get built, numbers get tracked, and reports get shared regularly. But in real business settings, decisions are often already leaning in a certain direction before the data is even checked. Sometimes…
Anyone else feel like BI dashboards look great but don’t really change decisions?
seen this across teams again and again. We build dashboards, polish metrics, align KPIs… and yet, in meetings, decisions still come down to gut feel or last week’s Excel sheet. On paper, BI is “live” and “data-driven.” In reality, half…
Why do machine learning models degrade in performance after deployment ?
Machine learning models are usually trained and validated in controlled environments where the data is clean, well-structured, and stable. Once deployed, the model becomes dependent on live data pipelines that were not designed with ML consistency in mind. Data can…
How do you resolve conflicting numbers across dashboards?
The solution is almost never choosing which dashboard is “right.” Instead, you investigate why they differ. Start by tracing lineage: what tables feed each dashboard, what transformations are applied, and where filters or aggregations diverge. Most conflicts come from subtle…
How do you identify and correct hidden biases within a dataset before analysis?
Bias can enter data through sampling errors, uneven user behavior, external events, or flawed data collection mechanisms. These biases can distort conclusions if left unchecked. Share a scenario where you discovered subtle but influential bias like a demographic overrepresentation, seasonal…
What’s the most common point of failure you’ve seen once an ML system goes live?
Once an ML system moves from a controlled development environment to real-world traffic, the very first cracks tend to appear not in the model, but in the data pipelines that feed it. Offline, everything is consistent schemas are fixed, values…
Business Intelligence or Artificial intelligence or both?
I am a new graduate and I am thinking whether to get into business intelligence profile or Artificial intelligence? I did read up on google. Is business intelligence stepping stone to world of data?
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MJ
Wrapo Biz
NA_analytics
- 3 years ago
Is MS Excel still in the game of reporting?
I am an experienced data analyst using MS Excel for years with VBA expertise. Do you think I should continue creating dashboards for it or learn one of these fancy tools of today? If yes, what should I choose?
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6
LookUpVisualizer
Razrap
- 3 years ago
Model is failing in spite of continuous training.
How and what can I do to train my model. My sample population doesn’t seem to work. My inputs don’t change that often.
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3
- 3 years ago
What is the best way to collect the data?
I have tried my best to collect data from surveys, questionnaire, interviews and group discussions. What else can be my choice? I follow the above model. Please suggest a better framework to better represent the collected data.
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3
- 3 years ago
Curious to know, what are the best tools on visualization in the market?
Have you used tools like Domo, Looker or Birst? Are these worth it according to you?
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3
Rajesh_Vincent
- 3 years ago
How to optimize steps in pentaho?
The current transformation does not run fast enough. The work is done but it takes longer than expected causing delays in the report generation. Any tips will help.
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1
- 3 years ago
Difference between analytics and analysis?
I am not from data background I am curious to know what really is the difference from the professionals, not the bookish definition of it.
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Sameer Barari
- 3 years ago
Analyst role in the companies
I have heard of data analysts who handle different set of things for different companies. A data analyst could be a data engineer or a data scientists or just into data analysis. What do you think is the actual role…
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2
- 3 years ago
R Web scraping issue
I am trying to enter keywords in a search field on a web page through R. Firstly I access link in R, use selector gadget to select the search field, extract keyword from list in R, ‘paste’ in search field…
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2
- 3 years ago
SQL – Recommendation needed
Hey guys, I’m currently studying Data Analytics and I’ve finally started writing SQL queries! Any recommendations for structured SQL learning?
Business Intelligence or Artificial intelligence or both?
I am a new graduate and I am thinking whether to get into business intelligence profile or Artificial intelligence? I did read up on google. Is business intelligence stepping stone to world of data?
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6
- 3 years ago
Is MS Excel still in the game of reporting?
I am an experienced data analyst using MS Excel for years with VBA expertise. Do you think I should continue creating dashboards for it or learn one of these fancy tools of today? If yes, what should I choose?
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6
- 3 years ago
Seeking Power BI Consultants/Freelancers for Partner Opportunities
Hi Folks- I recently launched a data platform designed for non-technical users. It’s a simple data hub for structuring, sharing, and collecting data. Other nice features: better data governance through reporting, data catalog, and sharing approval workflows, row level access…
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5
Kavya Iyer
Shweta Dubey
- 3 years ago
Resources to Learn Data Science
A collection of the best courses, books, and tools to learn data science.
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5
- 3 years ago
What benefits come with employing a developer for Power BI?
Hire Power BI developer with cross-functional knowledge has several benefits, one of which is a deeper comprehension of various business processes and their interconnections. These developers are able to produce dashboards that serve several departments, guaranteeing that different stakeholders receive…
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4
- 3 years ago
Do you prefer heavy data transformations during early ETL or later in modelling? Why?
I’m exploring best practices in designing data pipelines and want to understand how different teams handle computationally intensive transformations. Some advocate for doing it early during ETL to keep models clean and fast, while others prefer flexibility and defer transformations…
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4
Sameena
Arindam
- 3 years ago
How do data visualization consulting companies ensure the scalability of solutions?
Data visualization consulting company ensures scalability by designing solutions that can grow with the business. They implement data models and structures that can handle increasing data volumes without compromising performance. Consultants also choose visualization tools that are flexible and capable…
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4
- 3 years ago
Barbershop & Salon Data Engineering
Hi Data World, Im a new business owner , and have opened up my barbershop for 4 months now. I have been in the industry for 15 years, and realize the power of data. How it can influence behavior and…
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4
Devansh
Shamayl
- 3 years ago
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4
- 3 years ago
Is data mining redundant now? Or are there still data miners out there?
Data mining is often described as the process of discovering patterns, correlations, and trends within large datasets to generate actionable insights. But in today’s context—where data is abundant and growing exponentially—how do we ensure that the patterns we uncover are…
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4
- 3 years ago
