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Necessary Tools for Data Analysis

by Ruby Gracy
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data analysis

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. With such multitasking, a specialist cannot do without specialized tools and services. The article contains useful tools that use various analysis methods 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 field, data analysis is the whole spectrum of organizing the collection, processing and interpretation of information that will help clarify the marketing strategy, reinforcing weaknesses and multiplying strengths. Marketers cannot do without data analysis. It will help you build educated guesses rather than relying on guesswork. With it, you can 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 and analysis tools come to the aid of analysts. All of them differ in the levels of detail and methods of data interpretation. The number of such tools is quite large. Each specialist chooses the one that corresponds to the tasks and with whom it is more convenient to work.

How to analyze correctly

The analysis process consists of several stages. The analyst should:

  1. Clearly state the purpose of the analysis. To do this, you need to decide on your own expectations and questions that need to be answered. You should understand exactly what data should be collected (for example, the number of visitors, orders placed, open letters, etc.).
  2. Collect information from various sources, combining it, cleaning it, organizing and systematizing it.
  3. Take care of the quality of the collected data by checking them for errors and omissions. If you skip this stage, then the further interpretation will not be reliable.
  4. Conduct work with the results: analyze and interpret them. It consists in compiling dashboards, reports or charts, as well as comparing them with expectations and originally formulated questions.
  5. Take action based on the results. The revealed insights should be used as a basis for building further work. This will help make your marketing strategy more effective.
  6. Repeat the entire cycle of the analysis after some time to check what has changed after the amendments. This will help to find out how effective they were and, if necessary, make new changes.

Most of the time is taken by the 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, the specialist must eliminate the very possibility of its occurrence. Using special data analysis tools, a specialist basically excludes the possibility of human error, because automates the process. It also saves a lot of time and guarantees accurate information.

To select the appropriate tool, the specialist should narrow down the search list. To do this, you need to define:

  • what type of data will be analyzed;
  • what goal should be achieved;
  • what level of detail is required.

After answering all these questions, you can proceed to the choice of tools. You can use the list of services that we have prepared.

Tools and services to help analyze data

Below are data analytics tools that will help in collecting, analyzing and visualizing data, indicating the principles of operation and main characteristics.


A program with enormous opportunities for analytics. And although some users are sure that using Excel you can only create tables and create forms, analysts will confirm that this is a universal tool. Excel copes with a variety of tasks: from small ones to processing big data using a plugin.

To analyze in Excel, you need to be able to use:

  • basic functions (VLOOKUP, SUMIF, AVERAGE, COUNT), filters, graphs, pivot tables;
  • the functions “Find and Replace”, “Text by Columns”, “Remove Duplicates” – to clean and process data arrays, bring them to the desired form;
  • Conditional Formatting, PivotCharts, Data Validation and Sparklines. This will help in creating flexible reports, mathematical and financial models;
  • hot keys – to save time;
  • Power Query, Power Pivot add-ins – for integrating data from external sources into Excel.

Excel’s powerful capabilities, along with its huge user base, make it indispensable for analysis.

MS Excel Power Query

This Excel add-in is a universal tool that allows you to import (search, send) external data into Excel from sources that are available online or through corporate networks, and then process them. Power Query is able to load data of various structures, formats, types from various sources.

Information can be downloaded from:

  • Internet;
  • files (Excel, CSV, XML, text or folders with metadata and links);
  • database 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 is endowed with the ability to import emails and analyze them in Outlook. For example, you can import mail and create a histogram by the number of incoming letters, which will allow you to highlight those customers from whom letters are most often received.

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 superstructure is difficult to learn and is used for the most part only by specialists.

Microsoft Power BI

A modern online product that can provide significant assistance to an analyst. MS Power BI allows you to:

  • quickly create interactive informative business reports and dashboards (on the web);
  • interact and analyze data with the possibility of collaboration, visualization;
  • receive auto-updating of BI reports and visualizations when data changes;
  • support query language, including Power Query. At the request level, interaction between users is possible;
  • create data catalogs with assignment of search indexes to them;
  • support mobile devices;
  • do interactive work.

The Power BI query language for business analysts is close to natural. It 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 – the implementation of intellectual analysis;
  • Dashboards – interactive work with data and visualization;
  • Publisher – presentation of audience data.

Pyramid Analytics BI Office is endowed with a number of features. It allows you to:

  • collaborative high performance analytics;
  • modeling;
  • interactive visualization.

It 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, reporting modules, dashboards, OLAP and tabular data analysis, predictive analytics have almost the same design with the above service.

Pyramid Analytics is one of the most powerful analysis tools. This easy-to-learn platform is endowed with wide functionality and allows you to work with a large number of sources.

MS SQL Server Business Intelligence Components

There are several integrated components that allow analysis within the system itself in Microsoft SQL Server. The most famous include:

  • MDS (Master Data Services) – includes tools and processes with which you can manage the master data (business data) of the company (products, services provided, customers, employees, technologies used, materials, etc.);
  • SSIS (SQL Server Integration Services) – performs migration and integration of various data;
  • SSAS (SQL Server Analysis Services) – inside SQL Server OLAP and data mining.

Tools that make it easier to work with SQL queries

The capabilities of SQL are much more powerful than those of Excel. Many Russian and foreign companies require analysts working in large businesses, banks and technology companies to know this language.

It is convenient to work with SQL queries in DBeaver, mySQL Workbench, HeidiSQL programs. Such queries allow you to collect data from several databases in one unloading at once, and sort the obtained values ​​using various filters. For example, you can easily download information on the sales of winter boots in the Moscow retail chain for the 4th quarter of 2020 or the 1st quarter of 2021.

Google Analytics

It is one of the most popular services for collecting data and analytics on visitors to web resources. To collect data, a special tracking code is used, which is embedded in the website code.

Information for analysis is collected from:

  • HTTP user requests
  • cookies;
  • information about browsers and operating systems.

The collected information in the form of a list of parameters is transmitted to Google Analytics own servers. It is analyzed and transformed into reports that can be seen by each user in the account he created in the service.

Along with the paid version of Google Analytics 360, there is also a free one. The latter allows you to collect no more than 10 million hits per resource per month. If there is a need to collect more hits, a paid Google Analytics 360 plan or another tool will do.

Google Analytics does not receive data from CRM and other services, except for the native Google, until they are manually imported. Request processing time takes 24-48 hours.


Allows you to track user behavior in real time and analyze it. For this, a model based on the events and profiles of these users is used.

Mixpanel is based on key variables:

  • events – what action did the user take on the site;
  • properties – what property of the perfect event;
  • user profiles – complete information about individual users.

Before you start collecting information, Mixpanel should create a tracking plan that takes into account the previously defined business intelligence goals.

The tool has its own storage with its own structure. The amount of data collected is limited: up to 2000 properties can be collected per user profile.

The free plan allows you to track up to 100,000 users monthly. For unlimited reporting, you should choose a paid plan.


A platform that allows:

  • track website visitors in real time, thanks to Kissmetrics Live;
  • analyze behavior;
  • divide the audience into classes;
  • store all information centrally, in one place.

The Kissmetrics JS library allows you to automatically track user actions:

  • visiting a web resource;
  • filling out forms on the site;
  • viewing individual pages of the resource;
  • what ads they click on.

Kissmetrics can track user profiles and their activity until the moment of registration on the site, as well as events, advertising campaigns, reports. However, the platform cannot be integrated with the Google product line.

Most often used by small and medium SaaS businesses and e-commerce services.


Provides services:

  • advertising analytics based on semantic analysis mechanisms;
  • behavioral targeting.

The service is equipped with Weborama BigFish, a semantic AI platform that allows you to analyze the actions of visitors (conversations, behavior, opinions) on web resources.

Weborama BigSea allows you to generate a database of users and then evaluate each of them by digital behavior.

In Weborama, you can combine data from CRM systems with behavioral information and, based on it, build a model that predicts user behavior. It makes it possible to activate those user audiences for which the risk of outflow is predicted.

As it becomes clear, there are a lot of specialized data analysis tools. Each analyst selects the most convenient services and works with them. Choose the data analysis tools that are right for you based on your goals and objectives. We hope this article will help you make the right choice. If you have any questions – ask. Do not forget to indicate in the comments the services you work with.

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