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Pinned Threads
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5
KnowledgeKingX
shweta
Alex
janhavi
pangaeaX
- 8 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
- 2 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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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
How do you combine customer feedback, support tickets, and behavior data reliably?
Customer analytics often combines structured information, purchases, retention, and usage, with unstructured data such as reviews, support conversations, and survey responses. NLP and language models can help categorize feedback at scale, but sentiment alone may not explain what customers actually…
Why does a model perform well offline but poorly in production?
A model can perform well during validation and still struggle after deployment. Changes in customer behavior, data distributions, upstream pipelines, or the way predictions are used can all affect real-world performance. The difficult part is identifying the actual cause rather…
When should you fix data quality at the source instead of adding transformation step?
A common challenge in analytics is dealing with inconsistent formats, duplicate records, missing values, and mismatched definitions across systems. Transformation tools can standardize much of this, but repeated fixes can turn into a growing collection of exceptions and workarounds. At…
What should an AI agent be allowed to do when it has access to business data?
Connecting an AI assistant to internal data is one thing. Giving an agent permission to query databases, update records, trigger workflows, or take actions based on its findings introduces a different level of risk. A read-only analytics agent, for example,…
Are dashboards becoming places to verify AI answers rather than discover insights?
Traditionally, a business user opens a dashboard, applies filters, compares trends, and tries to understand what changed. With conversational AI and natural-language analytics, users can increasingly ask a question and receive a summary directly.That raises an interesting question about the…
If AI can write SQL and build reports, what should junior data analysts focus on learning?
AI tools can now help with SQL queries, data cleaning, visualizations, and report generation. That changes the learning curve for people entering analytics, but it doesn’t necessarily remove the need to understand the data or the business problem. I’m curious…
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…
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
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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5
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
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
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
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4
- 3 years ago
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 monitoring strategies help you decide when updates are needed?
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4
- 3 years ago
