Data analysis has been the hot topic in this digital era, but what really is big data? How could we use data insight to improve decision-making? Keep reading as we are going to breakdown the 3 key actions of big data application with real life examples, and the best practices on your big data journey.
What really is Big Data?
In short, big data is larger, more complex data set from a range of structured and non-structured data source.
Structured data is data that adheres to a pre-defined data model and is therefore straightforward to analyse. Examples of structures data includes Excel files or SQL databases.
What define Big Data are the characteristics commonly referred to as the 4Vs:
Unstructured data is the ‘human information’ that either does not have a predefined data model or is not organised in a pre-defined manner, and it is of the most concern and accounts for 90% of Big Data information. Examples of unstructured data includes things like video, audio or image files, as well as log files, sensor or social media posts.
Vpon is a leading big data company in Asia. with up to 21 billion daily biddable inventory and massive data accumulated from 900 million unique devices across APAC. Our data solutions include data analysis, brand marketing, cross-region expansion and data activation.
How Big Data Works?
As the wave of digitalisation ushers in, there is an increasing demand of data usage and application. The IDG report points that the collective sum of the world’s data grows in a rapid pace, and we can expect 175 zettabytes (1ZB = 109TB) of data worldwide by 2025, which is 175 trillion gigabytes!
While most businesses and public agree and acknowledge the importance of bi data, only few businesses process the data information effectively. This involves four key data actions: collections, analysis, application and integration. To maximise the data insight, businesses should first analyse the collected data, then apply and integrate the insights into their industry.
So how do we analyse Big Data?
Businesses across different industries wonder how each of them could use big data for business development and decision making. How could one be certain that the data are being used in the most effective way? This can be done through Vpon’s data solution, which includes data collections, data analysis and data application.
1. Data Collections
There are various ways for a business to collect data, other than the traditional user database and survey, tracking browse activities on website and app, IoT usage etc. can also collect first-party data. On the other hand, external user data is becoming more popular in the market too. This includes second-party data that are acquired from a trusted partner, and third-party data that are acquired from a data aggregator.
When there is a high variety and volume of user data, a massive data storage will be needed. To fulfil this basic requirement of big data, more and more businesses are turning into cloud service for a relatively flexible and expandable storage solution.
2. Data Analysis
Data from multichannel source are usually raw data that includes structured and unstructured data. Raw data cannot be used directly, they would first be centralised in a system called ‘Data Lake’ until a data engineer or a data scientist process them by:
Due to the complexity of the information, data analysts would then have to inspect, cleanse and transform the raw data through flexible programming languages (i.e. Scala, Python and R). Once the raw data is transformed into structured data, they will be organised and stored at a ‘Data Warehouse’, Apache Hive is the most used big data warehouse.
And finally, big data analysts could efficiently complete the analysis with either a descriptive analysis or predictive analysis through SQL (Structured Query Language), and curate a solution for optimisation and improvement.
3. Data Application
Visualising analysed data and validates with responding actions. Commonly seen data application in business includes user grouping, data report and data dashboard. Through big data analysis and AI algorithm, one could label users based on their type, behaviour, preference and actions, to distinguish the fittest user group for marketing purpose.
Data report is an extract of valuable insights and perspective found in big data, it is extremely useful for supporting decision-making and planning problem-solving strategies. PDCA (Plan, Do, Check and Action) is an example of iterative design and management method used in business. The model is useful for the control and continuous improvement of the data report usage.
Similarly, data dashboard is a strategy-supporting system with customisable and interactive user interface. Businesses could explore countless data sorting and grouping result and pick up insights that support upcoming marketing directions and planning.