SQL : PostgreSQL

  Aggregate Functions Like most other relational database products,  PostgreSQL  supports  aggregate functions . An aggregate function computes a single result from multiple input rows. For example, there are aggregates to compute the  count ,  sum ,  avg  (average),  max  (maximum) and  min  (minimum) over a set of rows. As an example, we can find the highest low-temperature reading anywhere with: SELECT max(temp_lo) FROM weather; max ----- 46 (1 row) If we wanted to know what city (or cities) that reading occurred in, we might try: SELECT city FROM weather WHERE temp_lo = max(temp_lo); WRONG but this will not work since the aggregate  max  cannot be used in the  WHERE  clause. (This restriction exists because the  WHERE  clause determines which rows will be included in the aggregate calculation; so obviously it has to be evaluated before aggregate functions are computed.) However, as is o...
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What can be automated?

 What can be automated?..




Task

Can it be automated?

Why?

Communicating with your team and stakeholders

No

Communication is key to understanding the needs of your team and stakeholders as you complete the tasks you are working on. There is no replacement for person-to-person communications. 

Presenting your findings

No

Presenting your data is a big part of your job as a data analyst. Making data accessible and understandable to stakeholders and creating data visualizations can’t be automated for the same reasons that communications can’t be automated.

Preparing and cleaning data

Partially 

Some tasks in data preparation and cleaning can be automated by setting up specific processes, like using a programming script to automatically detect missing values.  

Data exploration 

Partially

Sometimes the best way to understand data is to see it. Luckily, there are plenty of tools available that can help automate the process of visualizing data. These tools can speed up the process of visualizing and understanding the data, but the exploration itself still needs to be done by a data analyst.

Modeling the data

Yes

Data modeling is a difficult process that involves lots of different factors; luckily there are tools that can completely automate the different stages.  



  • Access to Python packages: There are many Python packages designed specifically to make life easier for scientists. Scikit-learn is an excellent package for scientists needing to make regressions, or implement machine learning. Numpy is a numerical package capable of performing most calculations that scientists would need. Matplotlib and Bokeh both offer plotting options with different features allowing flexibility in plot creation. Pandas replaces the Excel table with DataFrames enabling the data to be structured and manipulated in a familiar manner.


If you’re just starting your research, use our Product Selection Tool. Our Technology Advisors can significantly shorten your software search by matching you with the top workflow automation software and business process management software. It’s free and takes less than five minutes.

Table of contents

Compare the best workflow automation software

Product NameDrag-and-drop BuilderMobile AccessElectronic Forms
ProcessMaker workflow automation logo.

ProcessMaker

Green checkmark.Green checkmark.Green checkmark.
Integrify workflow automation logo.

Integrify

Green checkmark.Green checkmark.Green checkmark.
Comindware Tracker workflow automation logo.

Comindware Tracker

Green checkmark.Green checkmark.Green checkmark.
Flokzu workflow automation logo.

Flokzu

Green checkmark.Green checkmark.Green checkmark.
Zapier workflow automation logo.

Zapier

Red no symbol.Red no symbol.Red no symbol.
Kissflow workflow automation logo.

Kissflow

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Nintex workflow automation logo.

Nintex

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Process Director from BP Logix logo.

Process Director

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TrackVia workflow automation logo.

TrackVia

Green checkmark.Green checkmark.Green checkmark.
Gravity Flow workflow automation logo.

Gravity Flow

Green checkmark.Green checkmark.Red no symbol.

 


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