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Pinned Threads
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KnowledgeKingX
shweta
Alex
janhavi
pangaeaX
- 7 months ago
Resources to Learn Data Science
A collection of the best courses, books, and tools to learn data science.
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6
- 1 year ago
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5
- 1 year ago
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4
- 1 year ago
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4
- 2 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
- 1 month 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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3
- 2 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.…
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3
- 1 year 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
- 1 year 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
- 1 year ago
When does a KPI stop being useful?
Many organizations build dashboards around KPIs that were defined years ago. Over time, teams align targets, incentives, and reporting processes around those metrics. The KPI becomes part of how performance is measured. The challenge is that businesses evolve. Customer behavior…
Can embeddings replace fine-tuning?
As embedding models continue to improve, many teams are solving domain-specific NLP problems using retrieval, semantic search, and RAG pipelines instead of fine-tuning foundation models. This raises an interesting technical question: At what point does improving retrieval stop being enough?…
When does feature engineering become data leakage?
I recently saw a discussion where a model achieved surprisingly high validation performance, only to fail badly in production. The root cause wasn’t the algorithm, it was feature engineering. Some of the engineered features were technically available during training but…
When does feature engineering become data leakage?
I recently saw a discussion where a model achieved surprisingly high validation performance, only to fail badly in production. The root cause wasn’t the algorithm, it was feature engineering. Some of the engineered features were technically available during training but…
What does a junior data scientist look like in 2030?
I’m not asking whether AI can replace every data scientist tomorrow. What I’m wondering is whether we’re underestimating how much the role could change over the next 5–10 years. Tasks that once required technical expertise, writing SQL, generating code, creating…
Anyone dealt with a churn model overfitting after retraining?
Looking for some advice from people who’ve run into this before. I retrained a customer churn model using the latest six months of data and saw a noticeable jump in training performance, but validation metrics dropped significantly. The model now…
Is a data science degree becoming a liability?
For computer science and data science students, the landscape is changing faster than most curricula. Is a data science degree becoming more valuable, or less relevant, in the age of AI?
Is a data science degree becoming a liability?
For computer science and data science students, the landscape is changing faster than most curricula. Is a data science degree becoming more valuable, or less relevant, in the age of AI?
AI Readiness Framework: What Enterprises Need Before Implementing Generative AI
Enterprise generative AI use cases are shifting from experiments to operational imperatives. So, using AI terms in marketing and PR is not enough. Instead, companies are investing in intelligent workflows and assistantages, autonomous copilots. Although digital pilots prove to be…
What’s the hardest data interview question you’ve actually been asked?
I have a data interview coming up and I’m trying to prepare beyond the usual SQL, Python, and statistics questions. Most interview guides focus on technical concepts, but I’ve noticed that many companies ask scenario-based questions that are harder to…
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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3
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
Resources to Learn Data Science
A collection of the best courses, books, and tools to learn data science.
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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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Kavya Iyer
Shweta Dubey
- 3 years ago
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5
- 3 years ago
Tools You Can’t Live Without
Share the tools that make your data workflow more productive.
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5
- 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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Sameena
Arindam
- 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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Devansh
Shamayl
- 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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- 3 years ago
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- 3 years ago
