Tools for Descriptive Analytics

Quiz

There are several descriptive analytics tools and applications available. Some of the popular and most widely used tools are as follows −

1. Business Intelligence (BI) Tools

Business intelligence technologies gather, process, and analyse large amounts of organized and unstructured data from both internal and external sources. Images, videos, books, social media posts, emails, files, and related things may be considered as data sources. BI tools gather this information using queries and can show it in user-friendly formats like reports, dashboards, charts, and graphs.

Tableau, Power BI, and QlikView are popular tools for creating reports, dashboards, and data visualizations. These tools can be used for data mining, data visualization, performance management, analytics, reporting, predictive analytics, and related tasks. As a result, employees may use this data to make more informed decisions based on forecasts, market trends, and key performance factors.

Advantages of Business Intelligence Tools

Microsoft Power BI, Tableau, Qlik, Dundas BI and Sisense are some of the most popular and most widely used Business Intelligence Tools. Business Intelligence tools assist business organisations in understanding business processes and their flow based on past data; it helps to take informative decisions, and agile steps toward accomplishing bigger goals.

Data Centralisation

Data centralisation refers to keeping data in a central place. Organisations collect data from different sources like databases, web portals, customer relationship management systems, data warehouses, enterprise resource planning systems and related one. To make sense of it all, you'll need business intelligence solutions that can aggregate data and give specific views (problems, trends, analytics) based on your queries or what you want to know.

Self-sufficiency

Self-sufficiency in business intelligence (BI) refers to an organization's ability to manage, analyse, and understand data without relying extensively on external consultants, vendors, or third-party services. Data no longer belongs solely to your company's IT personnel. Employees without technical knowledge, including interns, can access and analyze data required for their particular teams. Achieving self-sufficiency in BI often entails many critical components −

In-House Expertise − Creating or employing a team with excellent analytical skills, data management expertise, and BI tool proficiency.
Training and Development − Continuously training employees to keep up with the latest BI tools and technology.
Integrated BI Tools − Implementing user-friendly and accessible business intelligence solutions for different departments inside the corporation. Self-service analytics tools allow non-technical users to generate reports and dashboards without requiring IT intervention.
Data Governance − Establishing explicit data management rules and procedures that ensure data quality, security, and compliance. This also includes creating data warehouses or data lakes to centralize and standardize data throughout the firm.
Automation and Scalability − Using automation to simplify data processing and reporting operations. This eliminates manual effort and allows the BI system to scale with the organization's growth.

Make predictions

Employees can make data-based informed decisions to easily access historical and current data. Predictive analytics and forecasting allow users to derive insights from a product's or service's performance history. If a business condition changes, intelligent tools can automatically detect anomalies, allowing you to respond to interruptions as they occur.

Automatic reports Generation

Many BI solutions are automated, so you don't have to manually enter data into Excel spreadsheets or switch between tools. If you need a report on a product over a specified period, the program will generate it for you. If the information is relevant and you want to use it in a presentation, you can construct interactive visualisations and download any charts or graphs you require.

Reduces business costs

Business Intelligence tools have to have the ability to do data analysis, consumer behaviour and sales forecasting; these tools also support real-time process monitoring to analyse, plan, and report processes. Most of the Business Intelligence tool customers stated these benefits helped them save money and improve revenue.

2. Excel/Google Sheets

Excel and Google Sheets are the most popular tools to do descriptive analytics, especially for small datasets. These tools are for descriptive analytics, which entails summarizing and interpreting historical data to uncover patterns, trends, and insights. These tools are effective and facilitate users for the following −

Data cleaning and organisation

This includes the removal of noisy and duplicate data and organising it in a structured manner to process and analyse it efficiently. It accomplishes the following −

Data Cleaning and Preparation − It organizes businesses historical data by applying sorting and filters features to focus on specific subsets of data.
Removing Duplicates − The "Remove Duplicates" features can help users clean their dataset by removing redundant data items.
Data Validation − Applying data validation rules to restrict input types or values will ensure data consistency and accuracy.

Basic Statistical Analysis

Statistical Analysis can be done using the following statistical analysis −

Descriptive Statistics − It encompasses functions like AVERAGE, MEDIAN, MODE, STDEV, and VAR to compute central tendency, dispersion, and other statistical metrics.
Frequency Distributions − Create frequency tables to determine how frequently specific values appear in your dataset. This can be accomplished with the COUNTIF or FREQUENCY functions.
Pivot Tables − Pivot tables are necessary for summarizing huge datasets. They let you easily calculate sums, averages, and counts, as well as group data into groups.

Data Visualization

Data Visualization features visualise data attractively and graphically; it helps to understand business scenarios using charts and graphs. Some of the key techniques of Data Visualization are as follows −

Charts and Graphs − Excel and Google Sheets include a variety of chart formats (such as bar, line, pie, and scatter) for visualizing your data. This aids in recognizing trends, comparisons, and patterns at a glance.
Conditional Formatting − Use colour scales, data bars, and icon sets to highlight important data points or patterns. This tool assists in swiftly identifying outliers or significant data trends.
Sparklines − These include mini-charts embedded in cells that provide a straightforward visual representation of data trends over time.

Trend Analysis

Trend analysis in descriptive analytics using Excel/Google Sheets are fin data over time to detect patterns, trends, and changes. This type of study is critical for understanding how metrics evolve and making sound judgments based on past data. It includes −

Moving Averages − Use moving averages to smooth out data volatility and highlight long-term patterns. This can be determined by using the AVERAGE function on a rolling window of data points.
Linear Regression − For more advanced trend analysis, use Excel's LINEST or TREND tools. This aids in projecting future values based on prior data.

Time Series Analysis

Time series analysis is a method of examining a data set gathered over some time. In time series analysis, analysts capture data points at regular intervals over a predetermined time duration. Time series analysis includes −

Time Series Graphs − Plotting time series data (for example, sales over months) aids in detecting seasonal trends or cyclical patterns.
Autofill for Time Periods − Use the auto-fill feature to quickly generate time series data points while maintaining uniform intervals for analysis.

Scenario Analysis

Scenario analysis is a strategy for anticipating future events and their possible results. It is applied in different sectors, including business, finance, and risk management. Scenario analysis includes −

What-If Analysis − Excel's What-If Analysis tools, including Data Tables, Goal Seek, and Scenario Manager, assist in investigating various scenarios and their potential outcomes. Google Sheets provides similar features.
Sensitivity Analysis − Creating sensitivity tables allows you to see how changes in input variables affect your outcomes.

Reporting and Dashboards

Dashboard reporting provides a visual depiction of your company's important performance indicators. Dashboard visuals use data from other reports to generate charts and graphs that provide an overview of your company's performance.

Custom Reports − Combine multiple tables, charts, and visualizations to create a thorough report. Both Excel and Google Sheets allow you to create dashboards that update dynamically as the underlying data changes.
Interactive Dashboards − Create interactive dashboards with slicers (Excel) or data validation (Google Sheets) that allow users to dynamically filter and analyse data.

3. Google Analytics

Google Analytics is a web analytics service offered by Google that monitors and reports on website traffic. It provides detailed information and insights into website visitors' activity and interactions with the site's content. This allows you to track website information such as bounce rate, conversion rates, traffic sources, and more. This tool is frequently used by website owners, marketers, and businesses to better understand and optimize their online presence.

Features of Google Analytics

Some of the key features of Google Analytics are as −

Traffic Analysis − Google Analytics keeps track of the number of visitors, their location (e.g., search engines, social media, direct traffic), and how they access and what access on your website.
Analysing User Behavior − It collects data about how users engage with your website, including pages they most frequently visit, how long they stay, how they navigate your site, and what actions they take (e.g., clicks, downloads, form submissions).
Finding Audience Insights − The platform provides demographic and geographic information about your users, including their age, gender, location, interests, and device kind.
To Tracking Conversion − Google Analytics can track particular goals like purchases, sign-ups, and other key actions for your business. This lets you discover how effective your website is at driving conversions.
Real-Time Data − It delivers real-time data, allowing you to view what is occurring on your site as it occurs, such as the number of active users and their actions.
Custom Reporting − Users can develop customized reports that focus on the metrics and characteristics most important to their business needs.
Integration with Other Tools − Google Analytics connects with other Google services, like Google Ads, Google Search Console, and Google Tag Manager, providing a more complete picture of your online performance.

Google Analytics is available in two versions − free and premium (Google Analytics 360), with the latter providing more advanced capabilities and better support for enterprise-level users.

4. Google Search Console

Google Search Console is a free service provided by Google that allows you to monitor, maintain, and troubleshoot your website's visibility in Google search results. This service allows users to track their site's traffic, view keyword performance, resolve difficulties, and receive Google messages about their website. It provides information on how a website performs in organic search as well as how to make changes to the site in the Google index. Unlike Google Analytics, Search Console only gives information on online search traffic, not additional segments such as direct traffic, traffic from adverts, or traffic from site referrals.

You do not need to sign up for Search Console to appear in Google search results, but it does help you to understand and improve how Google perceives your site. To make any necessary changes, Google Search Console allows you to track the phrases that have driven traffic to your website in real-time.

Features of Google Search Console

Some of the key features of Google Search Console are as follows −

Performance Reports − They provide precise information about your site's performance in Google Search, including measures such as total clicks, impressions, average click-through rate (CTR), and average position. You can monitor which inquiries are generating visitors to your website, which pages are working well, and so on.
Index Coverage − This tool shows you how many of your site's pages have been indexed by Google, as well as any issues that are preventing other pages from being indexed. It also offers information about faults, warnings, and legitimate pages.
URL Inspection Tool − This application lets you see how Googlebot evaluates a certain URL on your website. You may examine if the page has been indexed, any faults discovered during indexing, and even request that the page be re-indexed after making changes.
Sitemap Submission − Google Search Console allows you to submit your XML sitemap to Google, which helps the search engine comprehend your site's structure and find new or updated material.
Mobile Usability − It gives information about any mobile usability difficulties your site may have, such as responsiveness or mobile-friendliness issues, which could affect how users interact with your site on mobile devices.
Security Issues − The application notifies you of any security issues Google discovers on your website, such as malware or compromised content. It also offers suggestions on how to resolve these concerns.
Link Reports − You can examine which sites connect to yours (external links) and which internal pages are most frequently linked. This helps you comprehend your website's backlink profile and internal linking structure.
Search Enhancements − It demonstrates how well your site performs with specific search features, including rich results, structured data, AMP (Accelerated Mobile Pages), and more.

Google Search Console is a useful tool for anyone who wants to improve their site's search engine optimization (SEO), track its health, and check that it follows Google's criteria.

5. Statistical Software

SPSS, SAS, and R, are all effective tools for descriptive analytics, which is the process of summarizing and interpreting data to detect patterns or trends. Tools like SPSS, SAS, and R are often used for more advanced statistical analysis.

The main functioning of SPSS, SAS, and R in descriptive analytics are as follows −

SPSS (Statistical Package for the Social Sciences)

SPSS is well known for its user-friendly interface, which makes it accessible to people who aren't programming specialists. It is commonly used in social sciences, healthcare, marketing, and other industries to conduct statistical analyses. SPSS provides a variety of descriptive statistics, such as mean, median, mode, standard deviation, variance, frequency distributions, and cross-tabulations. It gives analytical results using graphical representations such as histograms, bar charts, and scatter plots. SPSS facilitates data manipulation, transformation, and cleansing, all of which are required before performing descriptive analytics.

SAS (Statistical Analysis System)

SAS offers powerful capabilities for creating descriptive statistics, such as summary statistics (mean, median, etc.), frequency tables, and customized reports. It also provides advanced data visualization features. SAS is well known for its ability to manage large datasets and complicated data transformations. It is widely utilized in various areas, including healthcare, banking, and government. SAS's PROC MEANS, PROC FREQ, and PROC UNIVARIATE procedures are frequently used for descriptive statistics, as well as more advanced analytics. This tool also provides substantial data management and transformation capabilities.

R Statistical Software

R is an open-source programming language and software environment that is commonly used for statistical computation and graphics. It is extremely customisable, with a large number of packages available for many types of analyses.

R has different functions for descriptive analytics or statistical analysis of data sets. It includes mean(), median(), summary(), and related functions. It also provides robust data visualization tools using packages such as ggplot2, which is well-known for producing high-quality graphs. R's dplyr, tidy, and data packages make it easy to edit, clean and prepare data for analysis. R is more popular among data scientists and statisticians because of its versatility and analytical depth.

6. Database Querying Tools

SQL-based tools allow for data extraction and summarization from relational databases. SQL-based database querying tools are critical for interacting with databases because they enable users to retrieve, manipulate, and manage data using SQL (Structured Query Language). These programs range in terms of functionality, ease of use, and applicability for various database types and use cases.

The SQL-based database querying tool you use is mostly determined by the database you are working with, your preferred working environment (GUI vs. command-line), and the complexity of your database administration requirements. For example, MySQL Workbench is fantastic for MySQL users, pgAdmin is ideal for PostgreSQL users, and DataGrip provides extensive cross-database support for more sophisticated users.

Some of the most popular SQL-based database querying tools are as follows −

MySQL Workbench − MySQL Workbench is a comprehensive database design and management tool for MySQL databases.
pgAdmin − pgAdmin is the most widely used open-source tool for administering PostgreSQL databases.
SQL Server Management Studio (SSMS) − SSMS is a free, integrated tool for managing SQL Server and Azure SQL databases.
DBeaver − DBeaver is a free and open-source database management application that supports a variety of databases, including MySQL, PostgreSQL, Oracle, SQL Server, and others.
Toad for Oracle − Toad for Oracle is a robust database management tool built exclusively for Oracle databases.
HeidiSQL − HeidiSQL is a lightweight, open-source SQL client for MySQL, MariaDB, and PostgreSQL.
Oracle SQL Developer − Oracle SQL Developer is a free Integrated Development Environment (IDE) for Oracle databases.
Sequel Pro − Sequel Pro is an open-source SQL database administration application for MySQL and MariaDB that runs only on macOS.
DataGrip − DataGrip is a powerful database IDE from JetBrains that supports a variety of SQL-based databases, including MySQL, PostgreSQL, Oracle, SQL Server, and others.

7. Mixpanel

This tool provides detailed information about how users interact with your website. It also provides details regarding how guests use their own devices while there. Mixpanel is a robust analytics platform that helps organizations understand how users interact with their products or services, notably through web and mobile applications. Unlike typical analytics systems that focus on page views and overall web traffic, Mixpanel is designed to capture user actions, or "events," which can provide deeper insights into user behaviour.

Some of the key functionalities of Mixpanel are as follows −

Event-Based Tracking
Focus on User Actions
User Segmentation
User Retention
Lifecycle Insights
Data Visualization
Interactive Reports
Detailed User Data
Personalization
API and Webhooks
Partner Integrations
Privacy and Compliance:
Data Security
User Consent Management

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