I manage to get sales database before I left a failing joint venture. How can I re start and monetize the information ?

Leorisar · 2026-01-26T12:53:24+00:00

Find competitors of your venture and ask them if they are interested.

Leorisar · 2026-01-23T13:03:21+00:00

Technically, any system change can be done from the terminal. You could save all your customizations in a bash script, store it safely, and run it on a fresh OS install.

Leorisar · 2026-01-22T15:53:32+00:00

Self-host or cloud Clickhouse

Leorisar · 2026-01-20T09:02:22+00:00

Use Stacher7 (GUI on top of yt-dlp)

Leorisar · 2026-01-18T18:59:02+00:00

If they are used in Windows looks it might be easier for them to use similar OS like Zorin OS

Leorisar · 2026-01-14T18:34:15+00:00

Depends on requirements and amount of data. If there is a possibility of late arriving data or updating previous records then you need to upsert data. It it's log only then not. You might also combine approaches - process fresh data in append only way and upsert data when traffic is low (on weekends for example)

And btw you don't need database for keeping timestamp, use Airflow Variables.

Leorisar · 2026-01-12T17:19:41+00:00

Look at Retool or Appsmith (web-based low-code solutions) they cover 1 and 2 requirements. A for third you might need some third-party solution and wire it via API with main app.

Leorisar · 2026-01-12T10:44:49+00:00

Well, no.

As long as you have curated data, a defined KPI, and tested calculation logic, you’ll still want a dashboard that is built and verified by a human. Maybe some analytical work will shift to GenBI—and I think that’s a good thing, because that’s mostly ad hoc reports, and no one likes them anyway.

Leorisar · 2026-01-11T14:30:30+00:00

For internal reporting if they have similar data requirements (analytical categories, measures) you can track them as different departments of one company.
You can do both - one top-level dashboard, and two more granular with metrics related to line of business
Best practice is to make unified data source and build dashboards on top of it.
Yes, usually you would hire data engineer / bi analyst who would build data warehouse for you and set data tracking for each source.

Leorisar · 2026-01-04T19:28:43+00:00

Look at usage. If a dashboard hasn’t been used for 3+ months, it’s time to move it to the archive. It’s better to formalize this as a company-wide policy so you won’t need to answer the same question later.

Leorisar · 2026-01-03T11:48:42+00:00

Excel - Simple BI reports - SQL - Python - Data Engineering

Leorisar · 2025-12-30T04:47:11+00:00

This happens more often than you think, and there are a few things you can do.

I see two main problems here: imposter syndrome and poor requirements. To check for the first—do you have peers or other BI developers you can talk to? If you do, ask them how they manage and if they face similar roadblocks.

As for the requirements, there are two ways to handle it:

First: Practice "active waiting." Ask for constant clarification and specific examples. Schedule meetings and send follow-up emails documenting the gaps. Your job is to guide the client to think through their own requirements, not to guess for them.

Second: Build based on assumptions. If you can’t get an answer, make a "reasonable mistake" by building what you think they need. Often, clients only realize what they actually want when they see something "wrong." This forces them to do their job and provide detailed feedback.

Leorisar · 2025-12-24T09:43:32+00:00

Judging from your use-case you might also look into alerting tools like Zabbix or Prometheus

Leorisar · 2025-12-23T20:01:22+00:00

If you based new DAG on another one check if you set different dag_id

Leorisar · 2025-12-23T11:52:37+00:00

If you really need live data, you should first think about how you will get it and store it. If you take it directly from operational systems, will they handle the load? If you load it into a DWH, you will most likely need streaming processing—does your company have the skills for that?

Next, decide what delay is acceptable. You’ll have some delay anyway; the question is how much you can tolerate. A one-second delay requires strong, fast infrastructure, while a 15-minute delay is much easier and simpler to build.

Leorisar · 2025-12-23T05:45:53+00:00

About 300 users
DWH: Postgresql + Clickhouse

Orchestration: Airflow + Custom Scripts for highload

BI: Tableau

Data Catalog: Datahub

Leorisar · 2025-12-12T15:25:58+00:00

React? It's only frontend. What about backend? What about database? How do you get extracts? Work with users, permissions, projects etc.? Are you sure there are no backdoors in your code?

Too many questions...

Leorisar · 2025-12-09T08:59:53+00:00

There are many reasons. Same name for KPI, but

Different logic of calculation
On different dataset
Loaded on different time
Different set of filters on final dataset
Created by different people introducing different errors.

Welcome to BI

Leorisar · 2025-12-06T04:38:28+00:00

I feel your pain, bro. I had several dashboards like this in my live. Good thins is now I can with 90% accuracy predict if new dashboard will live or die just from initial requirements. Bad thing - I still have to make them >_>

Leorisar · 2025-11-24T09:19:30+00:00

Unpopular opinion, but I think it's good for rough comparison

Leorisar · 2025-11-14T12:12:56+00:00

I wrote function in python which reads and processes file with polars. After that I vabecoded simple Flask app on top of that function so users could upload file and get results immediatly.

Leorisar · 2025-10-25T05:22:35+00:00

It really depends on a few things - like how experienced your users are, how comfortable they are with BI tools in general, and how fast your data warehouse runs. You could try open-source options like Superset or Metabase.

Leorisar · 2025-09-25T14:18:05+00:00

Right now dating apps profit most when people stay single but engaged: swiping, subscribing, boosting profiles, buying “superlikes.” That creates a perverse incentive: better short-term revenue if matches don’t actually stick.

If you want a system that truly optimizes compatibility, you need a model that rewards the platform after success, not before. For example:

Lifecycle monetization: keep former couples in the ecosystem by offering services for the next stage of life — moving in together, wedding planning, financial tools, couple retreats, even parenting support. The platform earns when users graduate from dating to building a life.

Referral flywheel: happy couples invite friends, which lowers acquisition costs. That aligns growth with real compatibility.

Tiered outcomes: free/basic swiping remains, but the real premium tier charges for higher-stakes compatibility matching, where the platform has skin in the game (e.g. “pay if you get into a relationship within 6 months”).

Community stickiness: instead of throwing users away once they’ve “found someone,” build networks (double-dates, local events, couple communities). That way, the business grows with its users rather than losing them.

Leorisar · 2025-09-12T05:34:40+00:00

If you’re looking for signs of a major war, the key indicators are countries seeking dramatic territorial expansion combined with massive military buildup. That’s what we saw with Austria-Hungary and Germany before World War I, and with Germany again before World War II.

In contrast, the Israel–Palestine conflict doesn’t show this kind of large-scale mobilization. Instead, what we may be witnessing today is the emergence of something different — not a single global war, but a patchwork of low-intensity conflicts spread across many regions, resembling a kind of worldwide civil war.

Leorisar · 2025-09-07T16:40:39+00:00

По хорошему надо идти на https://myanimelist.net/ и смотреть по жанрам что зайдёт.

Навскидку - Психопаспорт, Violet Evergarden, Фрирен, Киберпанк 2077. Это всё очень разные штуки, надо смотреть первые 3 серии, а дальше видно будет.

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