5 Types of Data Analysis Services Your Business Needs Today

225

Big Data is the driving force behind all business decisions. Enterprises, scale-ups, and start-ups, all equally rely on data analysis services to make insight-based decisions. 

A report states that the Big Data analytics market size is expected to grow to USD 745.15 billion by 2030. Companies today can easily access a large volume of self-generated data from several sources. But, this data is only effective if it is correctly interpreted. 

Businesses must bifurcate which data is helpful and which isn’t. This is where businesses need data analysis services. You must already know what is data analysis services. However, did you know that there are 5 types of data analytics your business can leverage? 

By collaborating with expert data analysis companies, you can leverage distinct insights that will help you make informed decisions. As one of the leading data science service providers, TRooTech Business Solutions has been helping businesses leverage data to make informed decisions and drive ROI and growth. 

By consulting with our team of experienced data scientists, data analysis experts, and consultants, we have made this list of 5 types of data analysis services that your business must consider investing in to withstand competition. Let’s explore them one by one. 

5 Important Data Analysis Services Types

Data Analysis Services

#1 Descriptive Analysis

This is the most common and basic type of data analysis services. Descriptive analytics extract value from previous data by breaking it into smaller units. Its main goal is to assist businesses in summarizing, describing, and understanding trends in data patterns. 

It enables businesses to analyze historical data by answering questions like “What happened previously” or “What was trending?” 

For example, imagine your organization’s previous month’s sales figures have gone down. Using descriptive analytics, you can identify the reasons behind this decrease in sales. Moreover, you can also hire leading data analysis companies to implement strategic actions. 

Key Benefits: 

  • Data Summarization: Businesses can break down large, complex data sets into smaller pieces of information which is easier to interpret. 
  • Decoding Data Patterns: It helps organizations identify trends and patterns in their data to make informed decisions.
  • Detecting Data Anomalies: Descriptive data analysis services help businesses identify unusual patterns within their data and detect inconsistencies. 
  • Access to Historic Data: Businesses gain access to the historical view of data. This helps them identify future trends. 

Use Cases: 

  • Analyze Sales and Revenue: Analyze which months or days had higher sales and modify the marketing strategy accordingly. 
  • Understand Customer Behavior: Gain insight into customer behavior such as preferences and purchase history. 
  • Market Data Analysis: Compare how your brand is performing against its competitors. 
  • Track Inventories: Analyze and track inventory levels, identify demand and trends, and optimize the supply chain. 

#2 Diagnostic Analysis 

Diagnostic analysis offers businesses insights into why a certain event happened. It helps businesses detect the root cause behind a particular problem or issue. It is used in combination with descriptive analysis or after it has been conducted. 

Key Benefits: 

  • Identify the Root Cause Behind an Issue: Businesses can analyze data and identify patterns, trends, and anomalies to understand the reason behind a specific problem. 
  • Multiple Applications: Diagnostic analysis can be used for multiple applications such as fraud detection, troubleshooting, etc. 

Use Cases:

  • Analyze Cause-And-Effect: Analyze customer purchase history, browsing behavior, and buying behavior to identify operational issues. 
  • Detect Supply Chain Issues: Identify the underlying cause behind delayed shipments, inventory stock out, and quality-related issues. 
  • Process Optimization: Identify areas for improvement and bottlenecks to improve process efficiency. 
  • Detect Frauds: Identify patterns and irregularities within data to detect chances of fraud.

#3 Predictive Analysis 

Predictive analysis is among the data analysis services that use statistical algorithms, Machine Learning, and other AI data analysis techniques for predicting future outcomes. It helps organizations make proactive decisions and offers insights into risks and opportunities. 

Key Benefits:

  • It uses AI data analysis techniques such as statistical algorithms and Machine Learning to assist businesses in forecasting future outcomes. 
  • Predictive analytics helps in identifying patterns and trends in data. 
  • It facilitates proactive decision-making for businesses. 
  • Organizations can use predictions to conduct risk assessments and identify potential opportunities. 

Use Cases:

  • Retail: Use predictive data analysis services to analyze data of their customers and forecast sales. This also assists in improving supply chain management. 
  • Financial Services: Detect frauds, carry out risk assessment, and identify scope for potential investment opportunities. 
  • Healthcare: Forecast future demand for medical services, detect at-risk patients, and improve patient outcomes through personalized care delivery. 
  • Manufacturing: Determine the chances of equipment failure, prevent unplanned downtime, and schedule maintenance. 

#4 Prescriptive Analysis 

We learned how predictive data analysis services can be used to make predictions about market outcomes. Prescriptive analysis takes this one step further. It is used to provide recommendations and suggestions to businesses based on outcomes forecast by predictive analysis.

predictive data analysis

Prescriptive analysis is a combination of predictive analysis and optimization algorithms, decision science, and other rule-based systems. Using this organizations can make informed, data-driven decisions. 

To put it in simple words, the prescriptive analysis answers the question “What should we do”. It analyzes available data and recommends a relevant course of action that will help your business achieve the desired results. 

Key benefits: 

  • Optimized Decision Making: Prescriptive data analysis services make use of mathematical algorithms and optimization techniques to determine the best possible solutions for a given scenario. 
  • Real-Time Analysis: Businesses can conduct real-time analysis to obtain recommendations and suggestions. 
  • Access to Dynamic Visualizations: Prescriptive data analysis services enable businesses to visualize insights and recommendations generated from data interactively. 
  • Integration With Analytics: Prescriptive analysis can easily be integrated with descriptive, diagnostic, and predictive analysis to support information-based decisions and actions. 

Use Cases: 

  • Optimizing Supply Chain: Companies can make informed decisions to improve inventory management, and production schedules, and optimize delivery and transportation routes. 
  • Detect Fraud: Businesses can analyze historical data to identify patterns and anomalies to easily detect fraudulent activities. 
  • Understand Customers: Businesses can understand their customers better by segmenting them based on their demographics, buying history, purchase behavior, browsing history, etc. 

#5 Cognitive Analysis 

Cognitive data analysis uses AI data analysis and Machine Learning algorithms to process and analyze large volumes of unstructured data. This includes data that is stored as text, images, audio, and video. 

The goal of cognitive data analysis services is to derive insights from complex or unstructured data sets. This is because these data sets are difficult to process by using traditional methods alone. 

Key Benefits

  • Natural Language Processing (NLP): Cognitive data analysis uses Natural Language Processing to gather insights from large data volumes. This includes data such as customer reviews, and data gathered from social media, etc. 
  • Deep Learning: Cognitive analysis also uses Deep Learning algorithms to predict future trends by analyzing existing data. 
  • Automation-Based Insights: Businesses can automate the insight extraction process with the help of cognitive analysis. This reduces the time and effort required to analyze large data volumes. 
  • Predict Future Events: By using Deep Learning algorithms, businesses can predict future events and outcomes. 
  • Integration With Tools and Platforms: Cognitive data analysis can easily integrate with other platforms and tools. Organizations can easily gather insights from multiple sources and combine them. 

Use Cases:

  • Healthcare: Anlayze medical images like X-rays or MRIs to easily diagnose diseases and identify potential health risks. 
  • Customer Service Operations: Businesses can analyze customer sentiment and feedback. This includes comments on social media, support tickers, customer queries and reviews, etc to identify trends and patterns within them that can be used to improve service. 
  • Retail: Businesses can analyze customer purchase patterns and buying behavior to optimize their inventories, customer satisfaction, and experience. 
  • Market Research and Analysis: Analyze customer data to obtain information and insights into customer behavior and preferences. 

If you are still uncertain about whether hiring data analysis service providers is the right move for your business, consider these advantages:

Why Are Data Analysis Services Important?

Big Data

  • They Help Data-Driven Decision-Making

Businesses can use data analysis software to identify current market trends and patterns. This helps them make better decisions when rolling out products and services. They can also optimize their sales and marketing campaigns. 

  • Organizations Can Boost Their Operational Efficiency

Data analysis can help your business identify the scope and area for growth through insights. Thus, you can easily identify pain points and areas for improvement. This helps reduce costs and increase productivity for your business. 

  • Identifying Newer Market Opportunities Becomes Easy

By collaborating with leading data analysis companies such as TRooTech, your business can identify new opportunities and areas in the market. This way, you can roll out products and services that specifically cater to customer needs. 

  • It Helps Businesses Optimize Customer Service

With data, you have a better understanding of customer pain points, needs, demands, and preferences. Your business can leverage these insights to improve and optimize customer service and engagement. 

Hire the Best Data Analysis Service Providers

To correctly implement data-based insights for your business, make sure you only hire data analysis service providers who have significant years of industry experience so that you can effectively utilize data-driven insights for your business operations.