# Quick search…

# Tutorials

# Data integration

# Tutorials and guides

# The best kind of question…

We are often asked what sort of questions we should ask the system, and how to phrase them. Ultimately, Telescope Labs works as an LLM. And we’ve done as much as possible to remove the need to do any “prompt engineering”.

In short - ask whatever you want, and we’ll aim to answer it using the data you’ve provided.

That being said, it’s still sometimes hard to get started. So, in addition to the “suggested questions” we provide on the homepage, here are some different skills that Telescope Labs has and some sample questions you could ask.

# Data retrieval & aggregation

Querying and searching raw data from connected sources, filtering and returning it.

Show me 5 example records from dataset ABC?

How many purchases came from Germany last year?

Calculate the total revenue of orders on 1st of April 2024

Which country do most paid users come from?

# Charting

Drawing charts and visualisations using the data

Draw a bar chart showing users by device type

Plot daily total number of quantity of orders in December

Draw a pie chart showing revenue by country

# Metrics

Using centralised definitions (e.g. from a semantic layer) and using these to answer questions.

Plot ARPU for the last 30 days

Plot DAU for the last year

# Trend analysis

Processing data trends, visualising and analysing them

Show me the trend of active users over the last month

What is the revenue trend over the last year in China

# Anomaly detection

Highlighting data points that are out of trend or expectation

Show me any revenue anomalies

Highlight any anomalous points on our D1 Retention

# Forecasting

Forecasting forwards using linear regression and statistical models

Plot ARPU for last month and predict next 7 days.

Predict LTV for the next month.

# Correlation analysis

Analysing historically, which data has correlated changes with others

What is the correlation between D1 Retention and LTV?

What is the correlation between Level completion and D30 Retention?

What is the correlation between marketing campaign and revenue?

We are often asked what sort of questions we should ask the system, and how to phrase them. Ultimately, Telescope Labs works as an LLM. And we’ve done as much as possible to remove the need to do any “prompt engineering”.

In short - ask whatever you want, and we’ll aim to answer it using the data you’ve provided.

That being said, it’s still sometimes hard to get started. So, in addition to the “suggested questions” we provide on the homepage, here are some different skills that Telescope Labs has and some sample questions you could ask.

# Data retrieval & aggregation

Querying and searching raw data from connected sources, filtering and returning it.

Show me 5 example records from dataset ABC?

How many purchases came from Germany last year?

Calculate the total revenue of orders on 1st of April 2024

Which country do most paid users come from?

# Charting

Drawing charts and visualisations using the data

Draw a bar chart showing users by device type

Plot daily total number of quantity of orders in December

Draw a pie chart showing revenue by country

# Metrics

Using centralised definitions (e.g. from a semantic layer) and using these to answer questions.

Plot ARPU for the last 30 days

Plot DAU for the last year

# Trend analysis

Processing data trends, visualising and analysing them

Show me the trend of active users over the last month

What is the revenue trend over the last year in China

# Anomaly detection

Highlighting data points that are out of trend or expectation

Show me any revenue anomalies

Highlight any anomalous points on our D1 Retention

# Forecasting

Forecasting forwards using linear regression and statistical models

Plot ARPU for last month and predict next 7 days.

Predict LTV for the next month.

# Correlation analysis

Analysing historically, which data has correlated changes with others

What is the correlation between D1 Retention and LTV?

What is the correlation between Level completion and D30 Retention?

What is the correlation between marketing campaign and revenue?

We are often asked what sort of questions we should ask the system, and how to phrase them. Ultimately, Telescope Labs works as an LLM. And we’ve done as much as possible to remove the need to do any “prompt engineering”.

In short - ask whatever you want, and we’ll aim to answer it using the data you’ve provided.

That being said, it’s still sometimes hard to get started. So, in addition to the “suggested questions” we provide on the homepage, here are some different skills that Telescope Labs has and some sample questions you could ask.

# Data retrieval & aggregation

Querying and searching raw data from connected sources, filtering and returning it.

Show me 5 example records from dataset ABC?

How many purchases came from Germany last year?

Calculate the total revenue of orders on 1st of April 2024

Which country do most paid users come from?

# Charting

Drawing charts and visualisations using the data

Draw a bar chart showing users by device type

Plot daily total number of quantity of orders in December

Draw a pie chart showing revenue by country

# Metrics

Using centralised definitions (e.g. from a semantic layer) and using these to answer questions.

Plot ARPU for the last 30 days

Plot DAU for the last year

# Trend analysis

Processing data trends, visualising and analysing them

Show me the trend of active users over the last month

What is the revenue trend over the last year in China

# Anomaly detection

Highlighting data points that are out of trend or expectation

Show me any revenue anomalies

Highlight any anomalous points on our D1 Retention

# Forecasting

Forecasting forwards using linear regression and statistical models

Plot ARPU for last month and predict next 7 days.

Predict LTV for the next month.

# Correlation analysis

Analysing historically, which data has correlated changes with others

What is the correlation between D1 Retention and LTV?

What is the correlation between Level completion and D30 Retention?

What is the correlation between marketing campaign and revenue?

In short - ask whatever you want, and we’ll aim to answer it using the data you’ve provided.

# Data retrieval & aggregation

Querying and searching raw data from connected sources, filtering and returning it.

Show me 5 example records from dataset ABC?

How many purchases came from Germany last year?

Calculate the total revenue of orders on 1st of April 2024

Which country do most paid users come from?

# Charting

Drawing charts and visualisations using the data

Draw a bar chart showing users by device type

Plot daily total number of quantity of orders in December

Draw a pie chart showing revenue by country

# Metrics

Using centralised definitions (e.g. from a semantic layer) and using these to answer questions.

Plot ARPU for the last 30 days

Plot DAU for the last year

# Trend analysis

Processing data trends, visualising and analysing them

Show me the trend of active users over the last month

What is the revenue trend over the last year in China

# Anomaly detection

Highlighting data points that are out of trend or expectation

Show me any revenue anomalies

Highlight any anomalous points on our D1 Retention

# Forecasting

Forecasting forwards using linear regression and statistical models

Plot ARPU for last month and predict next 7 days.

Predict LTV for the next month.

# Correlation analysis

Analysing historically, which data has correlated changes with others

What is the correlation between D1 Retention and LTV?

What is the correlation between Level completion and D30 Retention?

What is the correlation between marketing campaign and revenue?

In short - ask whatever you want, and we’ll aim to answer it using the data you’ve provided.

# Data retrieval & aggregation

Querying and searching raw data from connected sources, filtering and returning it.

Show me 5 example records from dataset ABC?

How many purchases came from Germany last year?

Calculate the total revenue of orders on 1st of April 2024

Which country do most paid users come from?

# Charting

Drawing charts and visualisations using the data

Draw a bar chart showing users by device type

Plot daily total number of quantity of orders in December

Draw a pie chart showing revenue by country

# Metrics

Using centralised definitions (e.g. from a semantic layer) and using these to answer questions.

Plot ARPU for the last 30 days

Plot DAU for the last year

# Trend analysis

Processing data trends, visualising and analysing them

Show me the trend of active users over the last month

What is the revenue trend over the last year in China

# Anomaly detection

Highlighting data points that are out of trend or expectation

Show me any revenue anomalies

Highlight any anomalous points on our D1 Retention

# Forecasting

Forecasting forwards using linear regression and statistical models

Plot ARPU for last month and predict next 7 days.

Predict LTV for the next month.

# Correlation analysis

Analysing historically, which data has correlated changes with others

What is the correlation between D1 Retention and LTV?

What is the correlation between Level completion and D30 Retention?

What is the correlation between marketing campaign and revenue?

# Tutorials and guides

# The best kind of question…

In short - ask whatever you want, and we’ll aim to answer it using the data you’ve provided.

# Data retrieval & aggregation

Querying and searching raw data from connected sources, filtering and returning it.

Show me 5 example records from dataset ABC?

How many purchases came from Germany last year?

Calculate the total revenue of orders on 1st of April 2024

Which country do most paid users come from?

# Charting

Drawing charts and visualisations using the data

Draw a bar chart showing users by device type

Plot daily total number of quantity of orders in December

Draw a pie chart showing revenue by country

# Metrics

Using centralised definitions (e.g. from a semantic layer) and using these to answer questions.

Plot ARPU for the last 30 days

Plot DAU for the last year

# Trend analysis

Processing data trends, visualising and analysing them

Show me the trend of active users over the last month

What is the revenue trend over the last year in China

# Anomaly detection

Highlighting data points that are out of trend or expectation

Show me any revenue anomalies

Highlight any anomalous points on our D1 Retention

# Forecasting

Forecasting forwards using linear regression and statistical models

Plot ARPU for last month and predict next 7 days.

Predict LTV for the next month.

# Correlation analysis

Analysing historically, which data has correlated changes with others

What is the correlation between D1 Retention and LTV?

What is the correlation between Level completion and D30 Retention?

What is the correlation between marketing campaign and revenue?