Analyzing data is both an interesting and complex process, during which it is better to acquire an appropriate arsenal. Therefore, today we are going to take a look at some cool tools. But more on that later.
Data analysis is at the heart of many areas of activity, including business and financial planning. An analyst cannot do without it when conducting analytical work, financial planning, building a marketing strategy and business planning. DataScience UA will help you to carry out such data analysis at a professional level.
If you want to complete this process yourself, then it is better to use the tools. With this kind of multitasking, a specialist cannot do without specialized tools and services. The article contains useful tools that use various methods of analysis to facilitate the work of an analyst. They will help not only in analysis, but also in structuring and visualizing data, and will be useful in project management. The presented tools will save time by automating the analysis.
Why do you need data analysis
In the marketing sphere, data analysis refers to the entire spectrum of the organization of collecting, processing and interpreting information, which will help to figure out a marketing strategy, reinforcing weaknesses and multiplying strengths. Data analytics are essential for marketers. It will help you make educated guesses, rather than relying on guesswork. It can help you identify trends, establish patterns, and find valuable information. This, in turn, will help optimize the workflow and advertising campaigns, and increase the profitability of projects.
Various specialized services, machine learning development company, and analysis tools come to the aid of analysts. They all differ in levels of detail and methods of data interpretation. The number of such instruments is quite large. Each specialist chooses the one that meets the assigned tasks and with which it is more convenient to work.
How to analyze correctly
The analysis process consists of several stages. Analytics should:
- Competently formulate the objectives of the analysis. To do this, you need to determine your own expectations and questions to which you need to get answers. You should understand exactly what data should be collected (for example, about the number of visitors, placed orders, open letters, etc.).
- Collect information from various sources, combining it, cleaning it, organizing and organizing it.
- Take care of the quality of the collected data by checking them for errors and omissions. If you skip this stage, then further interpretation will not be reliable.
- Carry out work with the results: analyze and interpret them. It consists in drawing up dashboards, reports or charts, as well as comparing them with expectations and originally formulated questions.
- Perform actions based on the results obtained. The revealed insights should be used as a basis for building further work. This will help make your marketing strategy more effective.
- Repeat the entire cycle of the analysis after a while to check what has changed after the amendments. This will help you to find out how effective they were, and if necessary, make new changes.
The most time consuming stages of data collection, cleaning and systematization. If this is done manually, then due to possible human error, the quality of the results obtained is significantly reduced.
Why use additional tools
To solve the above problem, a specialist must eliminate the very possibility of its occurrence. Using special tools for data analysis, a specialist, in principle, excludes the possibility of human error, since it automates the process. It also saves a lot of time and guarantees accurate information.
To select the right tool, the technician should narrow down the search list. To do this, you need to determine:
* what type of data will be analyzed;
* what goal should be achieved;
* what degree of detail of the analysis is needed.
Having answered all these questions, you can start choosing the tools. You can use the list of services that we have prepared.
Tools and services to help you analyze data
Below are data analytics tools that will help in collecting, analyzing and visualizing data, indicating how they work and the main characteristics.
Excel
A program with colossal analytics capabilities. And although some users are sure that Excel can only be used to create tables and create forms, analysts will confirm that it is a universal tool. Excel handles a wide variety of tasks, from small tasks to big data processing using a plugin.
For analysis in Excel, you need to be able to use:
* basic functions (VLOOKUP, SUMIF, AVERAGE, COUNT), filters, graphs, pivot tables;
* functions “Find and replace”, “Text by columns”, “Remove duplicates” – to clean and process data arrays, bring them to the desired form;
* Conditional Formatting, Pivot Charts, Data Validation and Sparklines. This will help you create flexible reports, mathematical and financial models;
* hot keys – to save time;
* Power Query add-ins, Power Pivot – for integrating data from external sources into Excel.
The powerful capabilities of Excel, together with a huge reach of users, make it possible to claim that it is indispensable for analysis.
MS Excel Power Query
This Excel add-in is a universal tool that allows you to import (search, send) external data to Excel from sources that are available online or through corporate networks, and then process it. Power Query is capable of loading data of various structures, formats, types from a variety of sources.
Information can be downloaded from:
* Internet;
* files (Excel, CSV, XML, text or folders with metadata and links);
* DB files (SQL Server, Access, Oracle, IBM DB2, MySQL, PostgreSQL, etc.);
* corporate repositories and public data sources;
* other sources such as SharePoint List, OData feed, Active Directory, Facebook etc.
Power Query has the ability to import emails and parse them into Outlook. For example, you can import mail and generate a histogram by the number of incoming letters, which will allow you to highlight those customers from whom letters come more often.
Power Query can work with tabular and multidimensional models. Able to connect additional sources. It has great functionality and is one of the strongest data analysis tools. But the add-on is difficult to learn and is used mostly only by specialists.
Microsoft Power BI
A modern online product that can provide significant assistance to analysts. MS Power BI allows you to:
* quickly create interactive informative business reports and dashboards (online);
* interact and analyze data with the possibility of collaboration, visualization;
* receive auto-update of BI reports and visualizations when data changes;
* support query language including Power Query. At the level of requests, interaction between users is possible;
* create data catalogs with the assignment of indexes for search;
* support mobile devices;
* carry out interactive work.
Power BI’s query language for business analysts is close to natural. Has an intuitive, friendly interface, easy enough to understand and master.
Pyramid Analytics BI Office
It is a cloud-based business intelligence platform with three key components:
* Data Discovery – implementation of intellectual analysis;
* Dashboards – conducting interactive work with data and visualization;
* Publisher – presentation of audience data.
Pyramid Analytics BI Office has a number of features. It allows you to:
* collaborative high-performance analytics;
* modeling;
* interactive visualization.
Has a Trial version and a cloud version (SaaS). Works with Big Data, integrates with R.
Some modules are very similar to MS Office products. For example, the modules for publishing reports, dashboards, OLAP and tabular data analysis, predictive analytics, have almost the same design as the above service.
Pyramid Analytics ranks among the most powerful analysis tools available. It is an easy-to-learn platform with a wide range of functionality and allows you to work with a large number of sources.
There are actually a lot of tools. Which one to choose is up to you based on your needs.
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