What is Data Anlytics?
In short, It’s making sense of data for effective decision making. Big data analytics includes an examination of large amounts of data to uncover hidden patterns, correlations and other insights. The known data analytics development cycle is described in stages:
- Descriptive (what happened) to diagnostic (why did it happen),
- Discovery (what can we learn from it), to predictive (what is likely to happen),
- Prescriptive analytics (what action is the best to take).
Big Data analytics can help organizations to identify and understand the data that is most important to the business and future business decisions. Data Analytics usually involve a large set of complicated data, that’s why it involves using specialized software tools and applications for data warehousing, predictive analytics, data mining, text mining, forecasting and data optimisation. Collectively these processes are separate but they are part of highly integrated functions of high-performance data analytics.
Why data analytics is so important for an organisation?
It is estimated that a whopping 73% of the company data goes unused for analytics. A company collects a huge amount of data and yet only 3% of business professionals are able to act on all the data available. According to a survey conducted by McKinsey, a data-driven or data matured organisation is 23 times more likely to acquire customers than its less-informed peers.
A data-driven organisation races to an average growth rate of 30% when compared to non-data driven organisations. Data analytics helps organizations leverage their data and use it to identify new opportunities It also leads to smarter business decisions, efficient operations, better profits and of course less complaining customers.
However 3 most immediate benefits of Data analytics would be cost reduction, Faster and better decision making, and launching new products and services.
What are the key features of Data analytics?
There can be many features of Data Analytics, however the key features must include the following.
- End Result formats or Dashboards
- Data processing which is collecting and organising data in a meaningful manner
- Data security or keeping company data secure
- Identity management or the people who will have access to data
- Technology support: use of various tools on the data like A/B testing or Easy integration of the tools.
If you are opting for a vendor to help you with data analytics, make use you check all the tick boxes for the features.
Are you late in implementing Data Analytics?
The answer we are afraid to tell you, but if you are starting now, you are already late. Before you look at above question, You may need to answer another question first.
How fast is data growing?
The IDC report said that the digital universe would double every two years until 2020. To quote another stat of IBM, we’ve created 90% of all data in just two years. According to IDC, by 2025, more than a quarter of all data created will be real-time, with 95% of that data generated by the Internet of Things.
According to the latest Digital report from 2019, internet users spent 6 hours and 42 minutes on the internet. Out of which social media accounts for 33% of the all the data consumed. You need to begin today, know what you need to implement data analytics in your organisation.
How you can sell internally to other stakeholders?
We understand change is important but difficult to implement. List a project which begins with low cost and high ROI. You may want to begin with financial reconciliations, Marketing process automations, Reporting automations. Run a pilot with us, explore and debate the benefits and implement.
Why Daas labs ?
We enable the business leaders to look at a meaningful, structured, patterned filled data so that they can take best decisions for the people and the organisations. We can help you define the data strategy for the organisation for the present and the future.