Whatever the area of work in which we move, there is something that we can be sure of; Marketing, finance, sales, operations… all the departments of a company can make good use of the immense amount of data that is collected on a daily basis; be it customer or user data, financial data, logistics management data. With all this we can predict attitudes, predict quantities, stock levels, etc. Buthow to extract and analyze all this data?
There are many options; from complex software such as RedShift, MapReduce or Hadoop, to more affordable alternatives to manage databases in small businesses. Startups take special advantage of this type of data analysis tools; up to 33% achieve more turnover and 12% experience positive growth, according to data from RJMetrics.
So let’s see what are the best ways to work with data:
Data analysis tools
1. Spread Sheets
Google launched its own ‘office pack’ and the truth is that it has become a major competitor of the famous Microsoft package. The main advantage with Spread Sheets: which would be the equivalent to Excel, is that your data is stored in the Cloud and you never lose them; if you forget to save, nothing happens because it updates itself; if you don’t have the document with you, nothing happens because you can access it from any computer… In short, it’s quick, easy and offers incredible results for certain tasks.
When to use it? It is suitable for almost anything, from keeping track of financial data, to monitoring positioning data, the evolution of orders, etc. It is not recommended to use it to do very complex operations.
2.SQL
SQL, or Structured Query Language, It is the youngest and most universal language used for interaction with databases. Although entrepreneurs often find it a bit intimidating, it is actually intended to be more accessible to less technical users. This tool, unlike SpreadSheets is very powerful when it comes to modeling complex data connections.
When to use it? This tool is good for making initial analyzes or respond to basic metrics.
3. Statistical software
With a statistical software we go one step further and we can perform linear variations and regressions that allow us to get results more specific and rigorous. Among the statistical software we have several options to choose from: SPSS, STATA or R they are the most timely, since they focus above all on offering data about the user or consumer; very useful for startups that want to improve their product or service.
When to use it? When you need to make data analysis tools to predict causality, decide between competitors or an outpost of the market. It is not recommended for beginners.
4. Visualization and Dashboard software
One of the things that most helps to structure the information is to be able to visualize it in a clear and orderly way, that’s why Visualization & Dashboard software is very important to be aware of where you are and what needs to be found out to move forward. These data analysis tools are not useful for scraping, but if the analysis is already finished and what you want is to translate it, then it is perfect.
When to use it? When we need to create complex stories, impact or show something to the world that is explained in data but it can be represented in graphics to be more visual and understandable.
5.Analytics
Most software on the market today has an embedded analysis system. This type of data analysis tools is very useful for collect data from a web domain and be able to visualize them easily and quickly. These ‘extras’ can be very efficient and save a lot of work. For example, an email marketer without much technical knowledge you can extract data such as the or impact on billing from these tools.
When to use it? this tool is perfect for creating the data collection, which can later be analyzed in other systems. It is recommended to use it only for individual web decisions or answering common questions about metrics. However, it is not the best alternative for make multivariate decisions or answer complex questions.
Although all these tools can be very useful, the key to taking advantage of the data is knowing how to interpret it. IEBS Business School launched the , an opportunity for companies to take full advantage of the new digital age.
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