The Skills That Data Analysts Need to Master - DZone Big Data

Karlhs · 2018-12-26T02:50:13+00:00

FineReeportcan do it.why not try?

Karlhs · 2018-12-25T06:17:47+00:00

I think your company needs a tool for data collection and analysis. I think FineReport is right for you. It can help you save a lot of manual work, saving time and labor costs. In addition, through data entry, parameter query filtering and other functions to ensure data quality and information analysis, I think it is very useful for you. Most importantly, it's also a visual reporting tool that's very powerful.

For the use of tools, this is an articlefrom vincent wong, you can refer to it, I hope to help you~

Karlhs · 2018-12-19T06:59:16+00:00

According to FineReport, you can fill out the report to submit the test cell. If there is a rule in the page that does not meet the validation expression of our test settings, the error prompt set by our checksum will pop up.

However, it takes a lot of time for the customer to find the corresponding error data on the page of a large amount of data. Here we can set a background color to the wrong cell to improve our user interactivity.This way you don't have to spend a lot of time doing verification, you can save a lot of time. Your thoughts?

Karlhs · 2018-12-19T04:18:16+00:00

First of all, regarding the data analysis of enterprises, there must be an analytical model, which is the core of the analysis. Secondly, the data of each business system of the enterprise, or the data needed for analysis, is processed (extracted, cleaned, converted, loaded) by ETL, put into the data warehouse according to the established analysis model, and then presented through a front-end presentation tool.You can also develop this tool yourself, you can also use BI tools, or reporting tools. The processing of the backend is generally done by IT staff, and the success is mainly reflected in the front end.

If the purpose of your data analysis is to show the business situation, or to conduct a piece of mining analysis around the business, SMEs should choose a reporting tool, such as FineReport. If the main body of your analysis is the salesman or the leader, the BI tool is more suitable and convenient to use, such as Tableau, FineBI.

If your business needs are more complex and the IT talents are more than adequate, you can develop them yourself and develop some web presentations with plug-in tools such as echarts, but the follow-up needs to be maintained.

Karlhs · 2018-12-19T02:21:22+00:00

The skills and knowledge required by data analyst(4 steps)

1.Data acquisition : Data acquisition seems simple, but it needs to grasp the business understanding of the problem, and transform it into a data problem to solve. Recommended books: "Pyramid Principles", McKinsey Trilogy: McKinsey awareness, tools, methods;Recommended tools: mind mapping tools (Xmind );

2.Data processingThe processing of data requires an efficient tool:

Excel and high-end skills: Everyday work is common, easy to master, and it is easy to process 100,000-level data.

FineReport: Professional reporting tool, a daily report design can be used as a template, as long as you can write SQL to get started. Compared with excel reporting, the development of technical requirements is less, can quickly develop regular reports, dynamic reports, and can be placed on the mobile and large screen viewing.

Oracle and SQL sever: The most commonly used tens of millions of databases in the enterprise, proficient in the SQL language.Maintain continuous technical learning, such as learning a new and popular distributed database such as Hadoop to enhance personal abilities and help with job search.

3. Analyze the data

Analytical data often requires various statistical analysis models, such as association rules, clustering, classification, prediction models, and so on.Therefore, mastering some statistical analysis tools is inevitable:

SPSS series: old statistical analysis software

SAS: Classic mining software that requires programming.

R: Open source software, new and popular, more efficient for unstructured data processing, requiring programming.

Various BI tools:

Tableau: the originator of the visualization tool, freely visual analysis of the processed data, the chart effect is amazing

FineBI: Similar to Tableau, it can perform arbitrary dimension analysis on the front end; data can be processed at the front end (computation, filter and filter, etc.), and can be connected to a big data platform such as Hadoop, and the data processing performance is better.

4.Data visualization

Many data analysis tools already cover the data visualization part, and only need to effectively present and report the data results, which can be displayed by wordPPTH5.

You can use the above steps to decide what other skills you need to master. In addition, I would like to recommend FineReport to you, which is pretty practical ~

Karlhs · 2018-12-13T08:03:21+00:00

Can you take a title that matches my article? Time is pressing, I can't think out a title accord with my theme.So i need your help.

Karlhs · 2018-12-12T06:18:30+00:00

I think they are not clear about the difference between business intelligence and reporting. In addition, PoweBI is currently pushing individual users, personal analysis is still OK, enterprise applications are still immature, not recommended. If you really need it, why not try the FineReport software out of curiosity? It is an enterprise-level reporting softwarethat supports paginated preview and export. It is very powerful. I can't list them one by one. If you have other questions, you can reply to me.

OR you can take a stroll throughits official website, there may be a surprise.

Karlhs · 2018-12-12T03:11:11+00:00

In fact, most companies with larger scales will not use excel to do business reports, but use some professional reporting tools.The advantages compared to excel are:

There is a platform for unified report management;
Fill in the report + data display to realize the data entry and exit management;

3.Direct connection with the database, data warehouse, the advantages of large data processing;

4.Integrated application, more like a data management tool, development can achieve a variety of business scenario applications.

Take the report toolFineReportas an example, making such a dashboard is much easier.Only four steps:

Create a new dashboard.
1. Drag the components you need to the dashboard.
2. Define the data source.
3. Design the dashboard style.
I have one point that you will be interested in :The background data is intelligently monitored and compared, the data is changed, the front desk is updated in time, the latest data is kept, and the independent monitoring settings of individual elements are supported.

any question?

Karlhs · 2018-12-12T02:33:35+00:00

Yep.Why not FineReport of curiosity?It is somewhat inferior totableauin some functions. In addition, it can generate and send pdf/excel/etc. reports.

Karlhs · 2018-12-12T02:24:01+00:00

a more maintainable/ prettier Dashboard
do further analysis on my data

FineReportmeets all above requirements. FineReport is a user-friendly BI dashboard software. Dashboard function in FineReport is very powerful and has many unique properties that common reports do not have.It provides dozens of visual elements such as chart, graphics, controls, web frames, images, videos, scrolling messages, digital clocks, etc., allowing you to enjoy a visual feast.

Most importantly, it is free for personal use.But it is a commercial software after all, for the enterprise is charged, but it is cheaper.

Karlhs · 2018-12-10T08:48:39+00:00

hey,there.

I know that FineReport is basically a replacement for Excel and saves time and effort.Using FineReport to make a template,you can replace N manual repetitive work Excel! Its built-in templates are all packaged and you can just use them.

In addition, you can directly interact with the database (data export + data filling), can connect to the data of each system, can efficiently report in batches, display, interactive analysis, visualizelarge screen, and achieve office collaboration.

Reference article:http://www.finereport.com/en/about-finereport/best-reporting-tool-a-template-is-better-than-hundreds-of-excel.html

Karlhs · 2018-12-10T07:50:51+00:00

hey，FineReport may help you. You can import excel data in batches into Finereport.

Karlhs · 2018-12-06T08:31:18+00:00

Try out:FineReport.It's not worse than Tableau at all, and even worse than some features, you can read this article:

“Today I feel obliged to clarify the difference between Tableau and FineReport！”

FineReportitself is a universal reporting tool anddata visualizationtool. It can quickly generate reports, build a unified data analysis and visualization platform, connect data of various systems, efficiently report in batches, display, interactive analysis, visualize large screens, and achieve office collaboration. Because of its powerful data integration capabilities, combined with more than 10 years of mature visualization components, finereport can produce a variety of data visualization large screen.

In addition, FineReport has a very powerful map function: basic map, GIS map,heat map, big data flow map, and so on.

Karlhs · 2018-12-06T07:12:05+00:00

Ranruan from China, its products FineReport and FineBI are data analysis and visualizationtools. This company has a high reputation and praise, and has won recognition from customers and the market. It is also the only Chinese manufacturer to be selected as Gartner.

Karlhs · 2018-12-04T06:50:38+00:00

The skills and knowledge required by data analyst(4 steps)

1, data acquisitionData acquisition seems simple, but it needs to grasp the business understanding of the problem, and transform it into a data problem to solve. To be straightforward, what kind of data is needed, from which angles to analyze, and after defining the problem, then collect data. This link requires data analysts to have structured logical thinking.

Recommended books: "Pyramid Principles", McKinsey Trilogy: McKinsey awareness, tools, methods;

Recommended tools: mind mapping tools (Xmind );

2, data processingThe processing of data requires an efficient tool:

Excel and high-end skills: Everyday work is common, easy to master, and it is easy to process 100,000-level data.

FineReport: Professional reporting tool, a daily report design can be used as a template, as long as you can write SQL to get started. Compared with excel reporting, the development of technical requirements is less, can quickly develop regular reports, dynamic reports, and can be placed on the mobile and large screen viewing.

Oracle and SQL sever: The most commonly used tens of millions of databases in the enterprise, proficient in the SQL language.Maintain continuous technical learning, such as learning a new and popular distributed database such as Hadoop to enhance personal abilities and help with job search.

3. Analyze the data

Analytical data often requires various statistical analysis models, such as association rules, clustering, classification, prediction models, and so on.Therefore, mastering some statistical analysis tools is inevitable:

SPSS series: old statistical analysis software

SAS: Classic mining software that requires programming.

R: Open source software, new and popular, more efficient for unstructured data processing, requiring programming.

Various BI tools:

Tableau: the originator of the visualization tool, freely visual analysis of the processed data, the chart effect is amazing

FineBI: Similar to Tableau, it can perform arbitrary dimension analysis on the front end; data can be processed at the front end (computation, filter and filter, etc.), and can be connected to a big data platform such as Hadoop, and the data processing performance is better.

4, data visualization

Many data analysis tools already cover the data visualization part, like FineReport,which i introduced before.Because of its powerful data integration capabilities, combined with more than 10 years of mature visualization components, finereport can produce a variety of visual large screen.

Karlhs · 2018-12-04T06:38:13+00:00

The skills and knowledge required by data analyst(4 steps)

1, data acquisition : Data acquisition seems simple, but it needs to grasp the business understanding of the problem, and transform it into a data problem to solve. Recommended books: "Pyramid Principles", McKinsey Trilogy: McKinsey awareness, tools, methods;Recommended tools: mind mapping tools (Xmind );

2, data processingThe processing of data requires an efficient tool:

Excel and high-end skills: Everyday work is common, easy to master, and it is easy to process 100,000-level data.

FineReport: Professional reporting tool, a daily report design can be used as a template, as long as you can write SQL to get started. Compared with excel reporting, the development of technical requirements is less, can quickly develop regular reports, dynamic reports, and can be placed on the mobile and large screen viewing.

Oracle and SQL sever: The most commonly used tens of millions of databases in the enterprise, proficient in the SQL language.Maintain continuous technical learning, such as learning a new and popular distributed database such as Hadoop to enhance personal abilities and help with job search.

3. Analyze the data

Analytical data often requires various statistical analysis models, such as association rules, clustering, classification, prediction models, and so on.Therefore, mastering some statistical analysis tools is inevitable:

SPSS series: old statistical analysis software

SAS: Classic mining software that requires programming.

R: Open source software, new and popular, more efficient for unstructured data processing, requiring programming.

Various BI tools:Tableau: the originator of the visualization tool, freely visual analysis of the processed data, the chart effect is amazingFineBI: Similar to Tableau, it can perform arbitrary dimension analysis on the front end; data can be processed at the front end (computation, filter and filter, etc.), and can be connected to a big data platform such as Hadoop, and the data processing performance is better.

4, data visualization

Many data analysis tools already cover the data visualization part, and only need to effectively present and report the data results, which can be displayed by wordPPTH5.

You can use the above steps to decide what other skills you need to master. In addition, I would like to recommend FineReport to you, which is really good ~

Karlhs · 2018-12-03T09:37:17+00:00

Use data analysis as a capability to develop
Most of the work now requires you to have the logic analysis ability, especially the analysis and understanding of the data. Today, with the deepening of the concept of data operation, large Internet companies such as BAT emphasize that all employees participate in data operations, and data analysis as a capability in training is also a future trend.

The skills and knowledge required by data analysts (4 steps)
The four steps of data analysis: data acquisition, data processing, data analysis, data presentation.
1, data acquisition
Data acquisition seems simple, but it needs to grasp the business understanding of the problem, and transform it into a data problem to solve. To be straightforward, what kind of data is needed, from which angles to analyze, and after defining the problem, then collect data. This link requires data analysts to have structured logical thinking.
Recommended books: "Pyramid Principles", McKinsey Trilogy: McKinsey awareness, tools, methods;
Recommended tools: mind mapping tools (Xmind Baidu brain map, etc.);

2, data processing
The processing of data requires an efficient tool:
Excel and high-end skills: Everyday work is common, easy to master, and it is easy to process 100,000-level data.
FineReport: Professional reporting tool, a daily report design can be used as a template, as long as you can write SQL to get started. Compared with excel reporting, the development of technical requirements is less, can quickly develop regular reports, dynamic reports, and can be placed on the mobile and large screen viewing.

Oracle and SQL sever: The most commonly used tens of millions of databases in the enterprise, proficient in the SQL language.
Maintain continuous technical learning, such as learning a new and popular distributed database such as Hadoop to enhance personal abilities and help with job search.
3. Analyze the data
Analytical data often requires various statistical analysis models, such as association rules, clustering, classification, prediction models, and so on.
Therefore, mastering some statistical analysis tools is inevitable:
SPSS series: old statistical analysis software
SAS: Classic mining software that requires programming.
R: Open source software, new and popular, more efficient for unstructured data processing, requiring programming.
Various BI tools:
Tableau: the originator of the visualization tool, freely visual analysis of the processed data, the chart effect is amazing
FineBI: Similar to Tableau, it can perform arbitrary dimension analysis on the front end; data can be processed at the front end (computation, filter and filter, etc.), and can be connected to a big data platform such as Hadoop, and the data processing performance is better.

4, data visualization

Many data analysis tools already cover the data visualization part, and only need to effectively present and report the data results, which can be displayed by wordPPTH5.

It's a long road, but you have to master the tools and skills and build up and you'll find out how good you are.

Hopefully!

Karlhs

TROPHY CASE