What is the experience of being a data product manager in the financial industry

​ In the background recently , The voice of the data product manager is getting louder and louder . Relevant industry and skill requirements have been systematically analyzed before , I won't repeat it here . This issue is specially invited to Mr.ang, Take you into the real working environment of data products , Personally experience and feel what a data product manager is like .

I started a , Let me introduce myself first .

I am about this year 4 Month of the month , Join my current company as a data product manager . And now it's three months away , Another three months will be a year .

Today, I'd like to share with you my experience as a data product manager for so long , Some understanding of data products , Including some mental journey of my work .

First, let me give you a brief introduction to data products , You may think that it sounds like data products are hanging in the air , It seems very complicated , But when you really do this job , This data product is not so mysterious .

In fact, data products have been widely used in the market .

For example, we can often use App, Like alipay 、 TaoBao , They are all very, very mature enterprises that use big data products ,App product .

such as APP Often give you some information , There are also some advertisements , For example, some advertisements , They all analyze some data from your background and then push it to you , Think you need some products .

Say something classic , Before, Netease cloud music was quite popular , It has a feature that works very well .

Guess you like this thing . It is actually a data product , For example, how did he guess the music you like , He can sing all the songs in his library , Then make a label , It's like giving every song from the singer 、 Give him a label for style , For example, pop music , Classical music , Then Jay Chou .

The labels on their products must be more detailed than I said , More rules .

Then you listen to some songs , Which songs do you listen to more often . He will listen to these songs through you , The data formed , Then analyze you , Form a user portrait for you , I recommend you the songs you like , This is actually a formation process of a data product .

My data products are not as complex as Netease cloud , We are more engaged in data products .

I work in a financial Internet company , Our main customer is mainly to provide some services to the bank , For example, bank loans , Credit business is lending money to others , It needs some data .

For example, he gives a loan to an enterprise , He needs to know whether the enterprise has any economic problems , Or how long the company has been operating on this basis , Then whether his business scope has any prospects in the future ？

These are the data of some enterprises , My company mainly provides these data to banks .

How did our general data products come into being ？

We will first understand the needs of customers , That is, what data products our upstream customers need , Then we take the first step to obtain the most basic data , We call it natural resource data . That is to say, from the industrial and commercial website , Or get these data from other channels .

When we get the data , There is no way to use the most basic data bank , For example, some basic data of enterprises , Its book information is also good , Or some other information , The bank has no way to use it directly , Then we need to give these data to him as the first step Do the cleaning , Is to mess up the data 、 Clean the dirty data .

Then they need some data , The data that is invalid to them is eliminated , Finally, we have to perform some operations on the data , It is better to calculate according to some rules they provide , Or other operations to achieve a data product , The data products they want .

After completion , Once this data product is formed, it will be provided to the bank .

Generally speaking, these data products are provided , We should also work with them to build a platform , Then provide these data by providing the platform at the same time , Through this platform, we provide data to them , It's usually like this .

What is our general workflow ？

First, connect with the bank , Then the bank's business teachers will communicate their needs with our project managers , What data do they want , For example, it needs to be visualized , Make some visual interfaces , To our project manager .

Our products need to communicate with the project manager about his needs , What can we achieve , What we cannot achieve for the time being , Then how to realize .

After communicating with the project manager , If there is anything unclear , We still have to communicate with the banking teacher .

After we have communicated with the project manager , We have to think about how to implement data products , How to deal with the data we have now , What bad things should be eliminated , For example, what rules should be made for dirty data , How to calculate these data , What is the format of the data .

Then go find the developer , When you design it . Find development and development to communicate , Explain what we are going to do , Then prioritize their work , After that, the development department can work .

When the development is completed , You have to check this data with the test , Data after development , Tell me where to test these tests , Because they don't understand business scenarios during development and testing , So they don't know what to pay attention to , All this needs you to tell them .

After communicating with them , After the test , Our data will be online , To the bank .

If the bank says there is no problem with the acceptance , The product goes online , If there is a problem with the acceptance at his side , We need to change it later , Then recycle the process .

The general workflow is like this .

Our daily work is probably a meeting or a meeting , Meeting with the project manager , The project manager will hold a meeting with the developer after the meeting , Hold a meeting with the test team after the development , That's it .

You may not know much about data products , I wonder if data products have high professional requirements on mathematics or other aspects .

In fact, data products require professionalism , For example, you used to be an ordinary product manager , You go to the data product manager , In fact, the challenge to you is not very big , You may not know what data products are like at the beginning , Maybe you should familiarize yourself with it first .

In fact, data products don't have very high requirements for professionalism , For example, if you want to process data , To understand some basic , These things are actually very easy to learn .

Then I need to know something, for example Excel How to process these data , Some basic functions , These things are very simple . I feel that the main competency requirements are similar to those of most product managers .

I think the most important thing is to know how to communicate , Because most of your work scenes are communication , Basically, I spend most of my time communicating , And your 80% All problems can be solved through communication .

As long as you understand your needs , You should first communicate your needs clearly with the project manager or business teacher , Then think about how to do these things well , How do you do it? , How to deal with . After these methods are thought out , Then communicate with your developers and testers , That is to say Communication is a very important ability .

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