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The 7 Best Data Analysis Tools That Will Change Your Perspective
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The 7 Best Data Analysis Tools That Will Change Your Perspective
Presented By
Black Pearl Matrix
The 7 Best Data Analysis Tools Are:
- Power BI
- Tableau
- Geckoboard
- Qlik
- Dundas BI
- Cyfe
- Grow
Data analysis is probably one of the most important resources a company has to obtain information from its customers, and data analysis tools help organizations to have greater accessibility to this data.
Currently, different companies require data to be processed and presented to support decision making, and data analysis systems are an increasingly important tool for marketing, commercial, business intelligence, among other areas.
The main analytics and dashboard platforms are in the cloud and can be connected to data wherever it is stored.
In this article, we’ll look at what data analytics is and why it has become such an important resource. We’ll also tell you which are the best analytics tools that will give you another perspective on your business.
SUMMARY
1- What is Data Analysis?
2- Tools for Data Processing
2.1 PowerBI
2.2 Tableau
2.3 Geckoboard
2.4 Qlik
2.5 Dundas BI
2.6 Cyfe
2.7 Grow
3- How does Data Analysis Benefit the Business?
3.1 Sales Strategies
3.2 New Product Development
3.3 Pricing Strategy
4- What Profile Should a Data Analyst Have?
4.1 Business Opportunities
4.2 Technical Knowledge
4.3 Communicative Skills
4.4 Critical Thinking
4.5 Data Representation
5- How does Data Analysis work?
6- FAQ – Frequently Asked Questions About Data Analysis Tools
7- Conclusion
1- What is Data Analysis?
Data analytics is a critical piece of decision-making, measurement, monitoring, and data control in your organization.
“Big Data” is a term that helps us describe the vast amount of data, structured and unstructured, that invades companies every day. But the most important thing is to know what companies should do with the information they receive, and the only correct answer is: analyze the data for better decision making.
Data analysis is the process of working with data, organizing it correctly, explaining it, making it presentable, and coming to a conclusion from your analysis.
2- Tools for Data Processing
Data processing tools must be viewed in a way that allows us to understand what story they tell us. And they must also be interpreted and understood by any member of the organization.
What are the tools for data analysis?
Data analysis tools are business intelligence tools capable of providing valuable information and data for your company. If you strategically analyze the valuable data it provides, you can grow, solve problems, and gather data from your business.
These are the tools we think have the best data visualizations:
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2.1 Power BI
One of the leading data analysis platforms is Power BI. This tool developed by Microsoft makes it simple for someone with no previous experience. You can create interactive charts and graphs from your business data.
It is designed for teams to work collaboratively. Power BI has a wide variety of templates and multiple display options.
Main Advantages of Power BI:
• Allows users to integrate their applications, provides real-time reports and dashboards;
• IT managers have autonomy to manage the systems that run this software;
• It has an excellent graphical environment to extract, transform and load information;
• Multi-device platform;
• Integration with the Office 365 package;
• Automatic analysis of information, offering correlations, outliers and data groupings;
• Integration with the Azure Machine Learning service;
• It is available in a free version and a paid version, starting at $10 per month.
2.2 Tableau
Tableau is a master of data visualization and analysis tools. It was acquired by Salesforce in 2019 but is still available in a free version known as Tableau Public.
It is considered one of the leaders in data visualization and also works as a comprehensive cloud-based analytics solution.
The essence of Tableau is the Excel PivotTable and PivotChart. Its design, color and user interface give us a simple and fresh feeling. It is designed to help the user make better decisions about the most efficient way to extract and communicate meaning from data.
2.3 Geckoboard
With Geckoboard, you can optimize data from spreadsheets, databases and other tools. It allows you to make presentations more clearly and easily.
Real-time metrics are easy to see and understand. This feature will help your team see the impact of your flash sales.
It has 60+ features and it is easy to create dashboards in this data analysis software.
You can filter the data to show exactly what you need and the user interface is intuitive.
The basic plan starts at $31 per month, but… the first month is absolutely free!
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2.4 Qlik
Qlik’s data analytics platform is used by over 50,000 customers worldwide. It has a free trial version, so you can try it out to see if it’s what you really need.
If you want to find unique business opportunities in the online marketplace, start exploring business intelligence software.
Main Advantages of Qlik:
• Offers unique data discovery through global data search;
• Data can be imported from sources such as Salesforce, Teradata and Hive;
• Full control of your data to prepare reports and export them in friendly software such as Microsoft Office.
2.5 Dundas BI
Dundas BI is a flexible business intelligence tool. It allows users to connect to multiple data sources in real time.
If your priority is data representation for the different areas of your company, this software may be of interest to you.
Main Advantages of Dundas BI:
• Excellent organization and presentation in tables, charts and data graphs;
• Ease of creating your own reports with only the KPI’s of interest;
• A good user experience on desktops, iPads and mobile phones;
• It has a support and support area for micro-enterprises.
2.6 Cyfe
Cyfe is a tool to analyze and process business data by connecting to different sources. If you have a digital strategy for online sales, this resource can help you.
Main Advantages of Cyfe:
• Possibility to monitor all the metrics of your digital channels in a single panel;
• Customize widgets and import files in CVS format;
• Historical data is stored in the system;
• It is an “all in one” application, as it allows you to extract data from different sources, such as Google or Salesforce, to see the behavior of your online sales;
• It has a free trial for 14 days.
2.7 Grow
The Grow data analysis tool lets you easily import and transform data from multiple sources into feed metrics and your dashboards.
It allows any business user to intuitively create metrics. You can filter, slice, and explore different types of charts as you browse the data to find the best way to get insights for your business.
If you want to improve your sales strategy, this data analysis tool can be of great help.
Main Advantages of Grow:
• Allows you to see how long you can accelerate your business growth;
• Can review historical data to measure growth and analyze sales behavior;
• All data is transmitted via SSL encryption;
• Sets a timer for the data refresh rate to handle real data in real time;
• Adds an executive dashboard so you have a visual summary of financial, operational and sales data;
• It also has a marketing panel that allows you to monitor the main metrics of Google Analytics, Adwords, social networks, CRM and email;
• It has a free trial and paid versions starting at $50 per month.
3- How does Data Analysis Benefit the Business?
As machine learning technologies get better and better at transforming and retrieving all that scattered data, E-commerce companies are starting to place more value on data analytics, which clearly benefits their business.
Here Are Some Benefits of Data Analytics in Business:
3.1 Sales Strategies
Data analysis improves cross-sell and up-sell strategies, generating greater revenue for companies.
Capturing and analyzing all interactions is a challenging but not impossible task.
Some data analysis tools can compile comprehensive user profiles: data-rich profiles of different audience segments.
This data analytics software captures every interaction a user has had with a brand, and this makes it possible to make product recommendations to customers.
Predictive intelligence recommendations can significantly improve your company’s bottom line. For example, Amazon’s product recommendation engine generates 35% of the company’s revenue.
3.2 New Product Development
Deciding on new product development is never an easy task for E-commerce companies.
Therefore, deep analysis and data research is needed to help us verify the feasibility of creating and launching new products in the market.
Each project must be supported by solid data that shows exactly what people are buying, what price they are willing to pay on average, and so on. Most believe they should pay at least five figures to some consulting firm for these surveys. But that is no longer the case. Data analytics platforms can provide all these insights at a fraction of the cost. You just need to learn how to interpret this data.
Thus, before venturing to invest in a new venture, it is essential to use data analysis platforms that support and support our future investment.
3.3 Pricing Strategy
Big Data analysis gives us access to more detailed information, which allows us to create a more efficient pricing strategy.
Pricing initiatives that are backed by data provide significant short-term results.
Big Data can bring substantial competitive advantages to any organization.
But to reap these long-term benefits, it’s important that the data is recompiled with a good data analysis matrix.
4- What Profile Should a Data Analyst Have?
The data analyst profile is one of the most requested today. And this is due to the digital transformation process that many companies are going through.
Many companies rely on data about their customers, products, processes, supplies and the marketplace. So these organizations need employees not only with great talent, but also with the ability to extract information, interpret and analyze data.
Here Are Some Skills A Data Analyst Should Have:
4.1 Business Opportunities
The role of the data analyst has to be broader and will have an impact on the company. Therefore, it is important that it be a profile that can see business opportunities through data.
You have to look beyond KPIs. While you don’t need to know everything, it’s important to develop business knowledge through your work. This will make you even more valuable as an analyst.
Business knowledge will improve your understanding of company data. You’ll be able to spot the early warning signs so you can act quickly.
4.2 Technical Knowledge
The data analyst must have technical knowledge of: software, systems and data. This profile must bring these elements together to extract meaningful insights from the data.
Technical understanding based on curiosity and interest are two important skills when choosing a data analyst.
Are you excited about taking raw data and turning it into something meaningful for your business? If yes, then you have a good profile for the position!
4.3 Communicative Skills
As a data analyst, we know that you will be communicating not only with data, but also with co-workers, vendors, management, etc. Therefore, it is important that you hone and strengthen your communication skills.
When the analyst shares information, it is essential that he uses the correct terms, without falling into technicalities that are often not understood by the other members of the organization. A good understanding will help develop ideas for making business decisions.
4.4 Critical Thinking
Critical thinking involves going beyond the technical tasks at hand. The data analyst profile should ask questions like “What impact will this data have on the business?” or “What are the buying trends of potential customers?” When they start questioning and asking hypothetical questions or answers, it helps them dig deeper into the data.
Observing and analyzing outliers should prompt further investigation. Let’s not forget that visual analytics can support your critical thinking processes because it allows you to see data from different perspectives and in the short term.
4.5 Data Representation
It doesn’t matter what tools the data analyst uses or whether they share their insights digitally or on a whiteboard. What is relevant is whether it manages to show what is happening in an image.
This profile should be able to get a correct representation of the data through a data graph, so that you can show all the findings clearly and easily.
The data analyst must be familiar with data visualization best practices and it is critical that he or she can apply these across the enterprise.
5- How does Data Analysis work?
As demonstrated, understanding what data analysis is and using it are extremely important processes for companies.
After all, this practice is responsible for taking advantage of all the potential of the information that a company has, transforming them into real opportunities for growth.
Still, many managers have doubts about using Big Data for business. See below the steps that must be followed during your analysis:
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- E-Commerce Store
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FAQ – Frequently Asked Questions About Data Analysis Tools
1. What is big data?
The definition of big data is data that contains greater variety, arriving in increasing volumes and with greater speed. This is also known as the three Vs. Simply put, big data is a larger and more complex set of data, especially from new data sources.
2. What are the 4 types of data analysis?
Descriptive analysis, Prescriptive analysis, Predictive analysis and Diagnostic analysis.
3. How to identify which are the valuable data that travels through the company?
Not all data is relevant and, therefore, it is necessary to establish key performance indicators (KPIs – Key Performance Indicators) and other specific, measurable, relevant and temporal metrics in relation to pre-established objectives, to be “fed” by this data.
4. What is the importance of good data analysis?
Analyzing the data allows you to better understand your brand's market and audience profile, what the trends are for your niche and how to design effective campaigns. This way, you will be able to devise safer and more assertive strategies, in addition to having greater long-term security for your business.
5. What is the main objective when analyzing data?
Data analysis is a procedure that aims to transform numbers and information into insights for decision making. Despite being used in different areas, it is in the corporate universe that the technique gains prominence.
Conclusion
Have you chosen yours yet?
There are a range of different data analysis tools available, and each one offers something a little different to the user – which one you choose will depend on a number of factors, including:
• Your needs;
• Knowledge of statistics;
• Coding experience.
We hope this information and data analysis tools can help you decide which type of tool is best for your business. But before you decide, it’s important that you answer this big question: what do you want to achieve?
If you have clear goals, you will find the right tool.
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