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Analytics in Big Data

by | Feb 23, 2022 | Blog

When making data-driven decisions, businesses need to understand and analyze their data. Thankfully, several different analytics tools can help with this. Companies can quickly get insights into customer behavior, market trends, and more by using the right tool for the job. In this blog post, we’ll look at some of the most popular analytics tools out there and how they can help your business. Stay tuned!

What is big data analytics, and what are its benefits for businesses of all sizes?

Big data implies three main concepts, 1) Compilation, 2) Dissemination and, 3) Exploitation. In its simplest form, big data analytics can be explained as a cycle of these three ideas.

Firstly, let’s simplify the idea of “big data analytics” further. Think about this, whenever you watch a Netflix, download a song, purchase an item, take an Uber or click on a link while searching on Google, you are compiling data. This data recognizes what, where, when, how, and why you produced that data. Hence, the information has value to the businesses and organizations that want to analyze and disseminate the data. Finally, organizations can exploit the data to facilitate our consumer behavior more effectively with a deeper understanding of spending patterns, tastes, and routines. And the cycle repeats.

Before digging deeper into big data analytics, it would be helpful to understand what precisely the term “big data” means. Big data can be sizeable complex data sets collected from several data sources. Data sets include but are not limited to a person’s height and weight, test results taken from a random grade 10 math class in Alabama, or the number of regular hamburgers sold in a day by McDonald’s at a given location in New Jersey or Kansas City. In sum, data sets can record any number of measured behaviors, actions, or decisions.

Since data sets include variables and number-values from all facets of society, when compiled, they are enormous! So large, in fact, that traditional data processing software can’t organize and disseminate it into practical, applicable information outputs. Therefore, data analytics is necessary to collect and analyze raw data so that individuals and organizations can make sense of it.

The majority of big data generated comes from three primary sources: social data, machine data, and transactional data:

  • Social data: is information that social media users publicly share, including metadata such as user location, language, biographical data, or shared
  • Machine data: is the digital information automatically created by the activities and operations of networked devices, including computers, mobile phones, embedded systems, and connected wearable products, such as watches and fitness accessories.
  • Transactional data describe an internal or external event or transaction as an organization conducts its business. Examples include sales orders, invoices, purchase orders, shipping documents, passport applications, credit card payments, and insurance claims.

What is the role of Analytics in big data?

The role of Analytics in big data describes the process of uncovering trends, patterns, and correlations in large amounts of raw data to help make data-informed decisions. In short, this is the dissemination stage. These processes use standard statistical analysis, such as clustering or regression against extensive datasets aided by analytic tools—for example, Excel, SAS, Apache Spark, Rapidminer, and others.

There are three types of analytics that businesses use to drive decision making:

  1. Descriptive analytics: Descriptive analytics are useful because they can provide insights into past This information can help businesses understand how their customers have interacted with them in the past, what products or services have been most popular, and where their customers reside. This information can help businesses make more informed decisions about their products and services and improve customer service.
  2. Predictive analytics: Predictive analytics are essential because they can provide insights into future events. This information can help businesses understand what products or services might be most popular in the future and where their customers might live in the future.
  3. Prescriptive analytics: Prescriptive analytics recommends actions companies can take to affect those outcomes.

How to collect and analyze big data using the latest technologies?

Companies capture data in many ways and from many sources. For instance, there are three ways to collect consumer data:

  1. By directly asking customers: An example of directly asking customers for data would be a survey that a business sends out to its customers to gain feedback about their experience.
  2. By indirectly tracking customers: One example of indirectly tracking customers would be using cookies on a Cookies are small files stored on a person’s computer and track their browsing behavior. This information creates targeted advertisements or tracks a person’s progress on a website.
  1. By supplementing with other customer data sources: For example, using data collected by rewards-program partners, online marketing analytics, or in-store traffic monitors, to name a few.

Individuals and small businesses can collect data via:

  1. Surveys: Surveys are one way you can directly ask customers for information. Surveys collect opinions, preferences, or Survey information helps to improve business decisions.
  2. Online Tracking: Online tracking is a way to collect data when individuals or small organizations visit websites through search engines or social media. Traditional tracking identifies who, where, and why someone went online, but most importantly, they collect specific online For example, suppose you visited the website of a competitor. In that case, your presence may be recorded with an ID number associated with your computer.
  3. Transactional Data Tracking: One way to track transactional data is by using cookies. Cookies are small pieces of data stored on a user’s They track a user’s activity on a website and generate a website traffic report.
  4. Online Marketing Analytics: Marketers use online marketing analytics to collect data about the visitors to their website. Marketers can allow third parties to build digital profiles by collecting information about visitor In particular, how often they visit, what sites they visit before they arrive at the page, and what visitors do on the site.
  5. Social Media Monitoring: Social media monitoring collects data by tracking the activity of people who visit websites through social media.
  6. Collecting Subscription and Registration Data: When individuals sign up for a subscription or register for an event, their contact information is often This information facilitates the creation of a customer database. The contact information can include name, email address, mailing address, and phone number.
  7. In-Store Traffic Monitoring: In-store traffic monitoring collects data by tracking the activity of people who visit For example, Walmart uses in-store traffic monitors to capture how customers move through the store and which sections are most popular. This information helps to improve store layout and design.

The different ways you can use big data analytics to improve your business performance?

The primary role of big data in any company is to make better business decisions. Modern big data analytics and operations anticipate the patterns of consumers. Search engines, in particular, Google, continuously track search patterns, purchasing decisions, and uses of information. Thereafter, they use those patterns to motivate brand loyalty and improve the overall customer experience.

Seven Tips on how to get started with big data analytics for your own business

  1. Who is visiting your company website?: Knowing the demographic characteristics of the people who consume your product or service helps you understand their needs.
  2. Which websites are no longer attracting traffic?: Understand which pages are no longer working allows you to improve web page content or discontinue web pages that no longer serve your clients’ needs.
  3. When using your website, at what point do customers leave?: By understanding what is causing people to leave your website, you can take steps to address the issue and improve your website’s usability.
  4. Which devices do visitors use when accessing your website?: It is helpful to know which devices your visitors are using because you can use that information to improve your website’s design and For example, if you know that most of your visitors use mobile devices, you can design your website for mobile devices.
  5. How are people able to find and access your website?: It is essential to know how people are getting to your website because it can help you make decisions about your product or For instance, if most people are going on google and typing in keywords, you can research which keywords you’re ranking on the first page. Google Analytics will show how many visits come from Facebook, Twitter, or other social media.

What is the Impact of Big Data Analytics on our lives?

The a mount of data we produce, by current estimates, is roughly 2.5 quintillion bytes of data each day. Big Data provides insights that reduce operational costs and optimize expenses for business, assist governments in designing programs, and allow consumers to make wiser choices.

When data is applied appropriately, it can improve the quality of life for people. For example, improving decisions and actions in business, health, education, entertainment, transportation, or energy consumption, will invariably lead to a higher quality of life. Hence, improving the quality of life should be the prime motivating force for organizations collecting and using data.

Big data analytics is the process of examining large data sets to uncover hidden patterns, correlations, and other insights. Applying big data in business leads to smarter decisions, more efficient operations, higher profits, and happier customers. We’ve seen how big data analytics can benefit enterprises; now it’s time for you to take advantage of this powerful tool. At Time Well Scheduled, we specialize in helping businesses harness the power of big data analytics. Our team will work with you to identify trends and opportunities hiding in your data and help you make better decisions based on those insights. Ready to get started? Contact us today!

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