What are the Best Types of Data Analytics? 

Successful businesses and leaders focus on constant learning and adaptability. No business and industry have led successfully without adapting and learning from the past. The Use of various types of Data analytics is the key to climbing the ladder by allowing yourself and your business to understand historical behavior and predict upcoming ones. That’s where data analytics comes in; to solve complex business challenges and analyze raw data to draw trends and insights for businesses which acts as a critical driver of business decisions.
Using a mix of data analytics can help draw relevant insights and support your business function in intelligent decision making.
1. Predictive Data Analytics 
Predictive data analytics is an advanced data analytics technique based on Analyzing past data to forecast future events to a degree of efficacy.
Predictive analysis can help make decisions regarding inventory, supply and demand, sales, and trends, finances, HR, and even global trends. It helps businesses set realistic goals to keep attainable timelines through effective business planning.
Predictive data analytics aims to share forecasts about what might happen to look at the trends and data and not predict the future.
Predictive analytics can improve the response time of governments, healthcare organizations, and emergency centers like NDMA and DOI.
Throughout the Covid-19 outburst, predictive analytics has played a vital role in healthcare organizations and response centers. The enormous data on covid-19 symptoms and their spread helped monitor trends treat patients with the worst symptoms, and forecast disease spread and risk severity.
Knowing the change in business dynamics, predictive data can support marketing teams in content creation, targeting relevant audiences, understanding behavior, and forecasting sales trends to plan campaigns.
2. Prescriptive Data Analytics
Prescriptive Data Analytics is the advanced form of analytics after predictive analytics.
The concept is based on:

  • Achieving best results for better decision making
  • Understand how to achieve business results through data

This type of data is proper, mainly when business entities focus on data-driven decisions.
The most familiar example of prescriptive data analytics is GPS technology, recommending shortest routes, the closest way to reach destinations for multi-billion tech giants like Careem. On the other hand, prescriptive analysis allows large businesses to schedule inventory, maximize production efficiency and improve customer experience.
Prescriptive data analytics has helped track patients’ pre-existing health conditions and determine future health risks, making it a game-changer for the healthcare industry. The data is helpful in multiple business units, including sales, finance, marketing, HR, and operations.
3. Descriptive Data Analytics 
Descriptive analytics is the most common type of data analytics and the foundation of all data types. It shows data in a meaningful way, including tables, bar charts, line graphs with (means, standard deviation, and variances).
Looking at the raw data and trends drawn, the descriptive analysis answers the question of “what happened?” Descriptive analysis helps draw meaningful representation to your data allowing you to understand why certain things or something happened. Leading to conclude valuable business insights.
They are the foundation of data reporting, and it is impossible to have Business Intelligence BI dashboards and tools without them. The informative data is collected through reports, metrics, and dashboards.
For example: Getting to know about sales in the past six months, a sudden increase in sales in one of your slow-moving products. That’s where descriptive analytics tell you which months and why the sales increased for a particular item.
An example of descriptive data is the insights generated from social media and websites where you find details about your target audience, engagement pattern, and how they must engage. Using social media data, businesses can measure trends from the past and derive results.
4. Diagnostic Analysis

Diagnostic analytics answers to “why it happened.” Once we understand what happened, diagnostic analytics helps us identify the causes and dig into the hidden problems with the descriptive analysis. It is considered an essential tool to get to the root of ongoing business issues.

Often known as Business Analytics, it provides businesses with information and insights on trends as to why they occurred and helps them in their decision-making processes. Diagnostic analytics uses data mining, correlations, regression analysis to discover problems that help business leaders and decision-makers make informed decisions.
The use of diagnostics can treat patients (illness and injury) based on the current symptoms they share. They can be used in the following other industries including:

  • To understand why customers’ demand for a specific product has increased
  • To know why conversion from social media ads has decreased or why are some ads performing better

Knowing how to use your data and make the most out of it should primarily focus on small and large-scale businesses. The data can intimidate business leaders and create actionable insights using diagnostic analytics.

What is Data Analytics?

Data analytics enables organizations to transform their business digitally, making them more innovative to improve their decision-making process.
Data analytics is heard among professionals, students, business people, and corporate leaders today as it is a crucial driver of success for businesses. Understanding how data works and the ability to draw meaningful insights is essential. The insights drawn from data help businesses and leaders make intelligent, actionable decisions.
Companies generate a massive volume of raw data daily through web data servers, transactions, customer feedback, social media, and external sources. This raw data is where data analytics convert into actionable insights, directly translating into improved business performance.
Data has become an invaluable means of measuring any business’ effectiveness. Businesses can make decisions using insights drawn from data with comprehensive views of market trends, customer needs, competitor analysis. They can embrace change and innovate business processes, products, and services by intensely studying their customer needs. Businesses can also forecast upcoming trends, and create value for all internal and external stakeholders, thus reducing risk.
Data-infused algorithms allow companies to monitor and evaluate new and existing customer responses and understand targeting for new product launches.
Data is needed for all businesses to improve their business performance and effective decision-making. It applies to all industries, including Manufacturing, Technology, Energy, Travel, Transport, Ecommerce, Logistics, and Healthcare. Data can help your customers, too, from picking an effective route while booking an Uber to managing inventory for small to large-scale e-commerce stores.

How Can Data Analytics Improve Business Decisions?

Data analytics and technology roadmap are essential tools in strategic planning for small and large businesses. By 2023 the market size is expected to grow by 80.57 billion USD.
Data has played a vital role in business management over the last decade. Its ability to solve complex problems and help make streamline workflow, identify fraud, and improve marketing for business growth help in faster decision-making. According to the Global State of Enterprise Analytics report, 56% said that data analytics helped in effective decision making at their respective organizations.
Using data, we can understand customer behavior from google analytics CRM software which can help in improved decision making and increase sales. Platforms like Google, Facebook, LinkedIn ask for age, location, referral leading to improved decision making on those customer profiles and allowing social platforms to personalize marketing and increase sales effectively. Well-designed dashboards enable better decisions and help managers and business leaders identify severe underlying issues and rectify them.
Using data analytics, businesses understand how their employees perform (weekly and monthly), leading them to streamline processes using insights and make better decisions.

History of Data Analytics and Technology Roadmap

Historically, analyzing data in the past was a manual and time-consuming task. Individuals and experts would check spreadsheets all day to gather insights. In the 1970s, businesses implemented electronic devices and technology to accelerate decision-making, including data visualization, web solutions, and algorithms. With the emergence of data, the demand and challenges increased from the increased number of competitors to technical challenges. Earlier, the data was unstructured and required significant sources to determine insights.

Who Needs Data Analytics? 

Organizations today are flooded with information and data. According to a Harvard Business Review survey in 2020, 89% say they analyzed data to their organization’s innovation strategy.
Individuals who benefit from data include:

  • Finance leaders use data to project a company’s financial performance in coming years
  • Marketers utilize data for market research industry trends, acquire new and existing customer data and create marketing strategies using the data.
  • The Human Resource function uses data to understand employee behavior patterns and improve diversity and inclusion at their companies. They also use data to gain insight into their employees.

To understand what type of data works in which situation, understand the types and which ones can benefit your company.

Types of Data Analytics

Data analytics gives valuable insights about business, customers, products, behavior, buying pattern, forecasting and acts as a great tool to mitigate risks. For best results, it is advised by data experts in the industry to opt for the most relevant approach.
Allowing businesses to understand the importance and achieve optimum results data can increase customer base and help to retain existing customers with custom offerings and discounts. To understand what types of data can support your business objectives, first implement data quality, access management, source identification, and data strategy according to business needs and what kind of analytics can nurture growth for your business.
Let’s explore the types of data analytics and how they make your business grow exponentially.
How Ascend Analytics Facilitates Businesses With Our Data Analytics Solutions? 
Are you interested in using data analytics for your organization?
Ascend Analytics facilitates businesses through consultation support by providing valuable insights from your data. We have supported businesses in multiple industries through extensive details and maintained the highest client satisfaction. We have conducted many data projects for eCommerce, fintech, restaurant, and SAAS companies. You can also learn to leverage the power of data for your business’s success.


1. How does Data Analytics improve decision-making?
Collecting and analyzing raw data regarding your customers and their interactions with your business lets you understand how your customers are similar. You can use this data to develop patterns and trends among your customers.
Using this data, you can develop strategies to enhance your various departments’ performances and make informed decisions. The above list is some of the various tools and processes used in data analytics, which run on automated algorithms.
Ascend Analytics can help you turn customer interactions into statistical data. We can also help put you in the best possible position to make informed decisions.
2. When should we deploy a Data Analytics strategy?
As soon as you have the data analyzed, you should consider data analytics strategies. There isn’t such a thing as “the right time” to strategize; however, it should follow the act of data collection and analysis.
Ascend Analytics can help you develop a strategy on the ideal time and deployment of policy and actions to process raw data into meaningful, actionable results.
3. Is there a difference between Business Intelligence and Data Analytics?
Business intelligence is all about the use of data to make better decisions. It is a process that collects, cleans, and analyzes data to provide information for decision-making. Data analytics uses data and statistical analysis to find patterns, trends, and other valuable insights.
Data analytics can be used for any business purpose or goal. Business intelligence can only be used for decision-making purposes as it uses the data mentioned above to develop make, actionable steps.
Choose Ascend as your data and business analytics partner. Our solutions are simple and can be a game-changer for your business.

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