BI software: data mining now within everyone's reach
Data analysis tools are gradually making their way into the corporate world, because although the interest is not new, software has evolved to become much more accessible. Over and above this trend, today's uses are moving towards data mining. Why and how? A tutorial on data analysis is in order: here's how.
Data mining: definition
Data mining encompasses all the methods, techniques and tools used to uncover knowledge from large volumes of data. Unlike Business Intelligence, whose aim is to create reports and dashboards to understand a situation and make decisions, Data Mining aims to uncover correlations and new , unknown information.
Revolutionizing practices with online BI software
Data mining has been around for a very long time. In fact, some believe that the first data mining operations were carried out by the Chinese emperors almost 4,300 years ago. The disruptive factor that produced the latest revolution in BI is the migration of data to the Cloud.
Indeed, the fact that companies' most important data is hosted on private or public Clouds changes the game in more ways than one:
- Data can be accessed via a simple Internet connection;
- Data can be aggregated in a single location;
- Data can be read in real time;
- Data archiving is unlimited in terms of time and volume, thanks to the decreasing cost of storage.
This technological breakthrough is also accompanied by the simplification of data mining tools. The American company Zendesk, with its Bime business intelligence tool, is a perfect example. It enables Web Marketers, Sales Managers and Controllers to create the dashboards they need to manage their business.
More concretely, this means that whoever is concerned with the data (the business) doesn't need to go through a Business Intelligence Analyst to query the databases and extract the information contained in the data. Bime features over 60 connectors that enable users to "plug in" to the data sources they need, and then create their own tables or cubes in the same way as a pivot table in Excel. These data sources include :
- Social networks: Twitter, Facebook, Linkedin, YouTube, Instagram, Vimeo ;
- Website data: Google Analytics, MySQL;
- Static files: Excel, CSV, Google Drive, DropBox, XML;
- Marketing software: Campaign Monitor, MailChimp, Zendesk, Salesforce;
- And many other sources
From Business Intelligence to Data Mining
Using a tool like Bime not only allows you to design interactive dashboards whose data can be read in real time, but also to gain a foothold in data mining thanks to easy-to-implement practices.
- The aggregation of multiple data sources enables statistical correlations to be identified between distant data. For example, by mixing Facebook data with e-commerce site data, we can discover that women are more inclined to make a purchase following a campaign on social networks, whereas men buy on the basis of product comparisons.
- The drill-down function enables data to be broken down into sub-segments. Let's take the example of a marketing campaign in France: the BI software will separate revenues by channel (Adwords, Emailing, Billboard), then take one of these channels and observe the results by city. The aim is to direct marketing budgets more effectively.
- The analysis engine's algorithm also enables trends to be identified (stagnation, decrease, increase), as well as forecasts incorporating seasonal factors. This makes it possible to capitalize on past results to anticipate future sales, for example.
Data mining is not an easy discipline. It requires a great deal of rigor and method. A tool like Bime, on the other hand, breaks down external barriers to the user, such as access to data without SQL queries or extraction, and data manipulation without formulas or manual calculations.
Explore your data in 4 simple steps
1. Define your problem
The first step is to focus your attention on the objective you wish to achieve. This could be solving a problem (e.g. understanding why sales are down in May), optimizing marketing budgets or improving a product.
It's also a matter of formalizing the graphs that will help us understand the problem.
2. Connecting and structuring data sources
Software such as Bime connects to data sources in two ways: by importing a file (CSV, Excel), or with logins and passwords when using a "Cloud" source. If you want to retrieve data from your website or any other private database, you'll need to add a step to break down the fields into two groups: attributes and measures. Attributes are names, words or identifiers, while measures are numerical values.
3. Creating queries and graphing them
Creating queries and graphs is the most time-consuming part of the process, since it requires not only the creation of queries, but also your analytical skills. Bime allows you to analyze a single data source or several on the same graph, thanks to Query Blender.
This tutorial explains how to get to grips with this component:
4. Dashboards and reports
The purpose of BI software is to formalize and disseminate results rich in "actionable" information. Users add the graphics of their choice to dashboards, which can be accessed by an unlimited number of readers via logins. The great advantage of a tool like Bime over a traditional Business Intelligence solution is that it offers access to data in real time: each time the dashboard is refreshed, it is updated with "live" data.
What are the business benefits of data mining?
Data mining goes further than simply understanding a company's business. It enables us to delve into unknown areas of a market or business that could potentially revolutionize the company's future.
Considering the price of a Bime license and the time required on the part of the user, data mining is a real opportunity to create competitiveness in companies. The collection of data and the resulting discoveries give market share to those who take an interest.
Conclusion
Data mining is now accessible thanks to ergonomic online Business Intelligence tools and the prosperity of data in the Cloud. This discipline has also moved from the hands of technicians into those of business managers more inclined to understand the information they are mining. Although the technical hurdles have fallen, data mining still requires method and rigor. Last but not least, data mining represents a real business opportunity for companies seeking to boost growth and competitiveness.
Article translated from French