Nitor Infotech Blog
Nitor Infotech is a leading software product development firm serving ISVs and enterprise customers globally.

As I begin writing this blog, I am pulled down memory lane where these famous lines from the poem ‘The Rime of the Ancient Mariner’ penned by Coleridge echo: ‘Water, water everywhere but not a drop to drink’… Perhaps today it might be fair to concoct this modern equivalent: ‘Data, data everywhere but hardly a drop to use’…?

Truth be told, data is everywhere, but in a raw form. Its value lies in the conclusions that we can glean from it. The answer to the question ‘How so?’ is data analytics!

Put simply, data analytics is the magical and compelling science of how raw data is transformed into something that is supremely useful for your organization. The data of your organization may be real-time, historical, unstructured, structured, or qualitative – analytics has got you covered.

In this blog, I am excited to share some thoughts on the types of data analytics, why you should put data analytics on your agenda, the difference between big data and data analytics, as well as what’s on the horizon for data analytics. So, without further ado, let’s dive in!

Types of Data Analytics

Take a look at these four major types of data analytics:

  • Descriptive Analytics – This category is what you need to opt for if you are looking for answers to the fundamental questions of ‘what’, ‘how many’, ‘when’, and ‘where’. Ad hoc reporting (that facilitates collaboration and decision-making) and canned reporting (prebuilt to respond to business questions) are the two kinds of descriptive analytics.
  • Diagnostic Analytics – It’s often extremely important (and interesting as well) to figure out why a specific event happened. Diagnostic data analytics is the process of examining data to do exactly that.
  • Predictive Analytics – In case your organization is already harnessing predictive analytics, you know that thanks to it, identifying trends, correlations, and causation can be a cakewalk. It offers predictions about future outcomes utilizing historical data integrated with statistical modeling, data mining techniques, and machine learning.
  • Prescriptive Analytics – This is a valuable tool in which AI and big data join forces. With promising evolution in machine learning, prescriptive analytics can step in to meaningfully respond to questions like “What if we try this?” and “What is the best action?”

As you can imagine and might have experienced, data tells a riveting story, and these four types could work in tandem to render a complete visual of this story. These days, organizations are going for leading-edge data analytics solutions with ML capabilities as they are looking to make enhanced decisions and narrow down relevant market opportunities.

Now that you have a fair idea of what the types of data analytics are, it’s time to turn to the ‘Why’ of data analytics…

Benefits of Data Analytics

With capabilities like business intelligence (BI) and reporting, data preparation, data visualization, predictive analytics, and even geospatial analytics, data analytics serves up evident benefits such as:

  • Steering business decisions
  • Personalizing customer experience
  • Streamlining operations
  • Maintaining quality as well as consistency
  • Improving security
  • Tackling setbacks with ease

In a nutshell, if you’ve been aiming to unlock key insights for your business, analytics is a good route to take. It’s natural to get slightly confused while using the terms ‘big data’ and ‘data analytics’. Here is a list of the major differences between the two…

Differences between Big Data and Data Analytics

Finally, let’s take a step forward and peek into what the future of data analytics holds…

The Future of Data Analytics

Data analytics has taken the wheel in the technology vehicle we are in, and for good reason. We should expect it to dramatically alter the ways in which we work and live. Be it in BFSI, healthcare, manufacturing, retail, or another industry, business users are likely to widely adopt data analytics. Its very welcome impacts include drops in costs and surges in business revenue.

As interconnectivity is becoming paramount for success, devising process strategies for maintaining data across all the systems of your organization is vital so as to maintain a competitive edge.

I hope my blog has helped you become familiar with everything that data analytics is and how it can support you in your endeavor to make your organization even more insight-driven!

Send us an email and visit us at Nitor Infotech to know more about how we accompany businesses in their journeys of digital transformation. Download this datasheet if you’d like to learn more about data analytics in the manufacturing realm and our areas of focus. Also watch this space for more blogs that will focus on the types of data analytics!

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