The big data applications enable the advanced analytics professionals including the data scientists in analysing and generating better and deeper insights for the businesses to make agile and informed decisions. These applications help process volumes of data, various forms of data, real-time data. Traditional BI & DW applications could only process data to a certain extent and hence the need for big data applications. Big Data applications have now become a norm across all industries.
At Indium we have vast experience in implementing big data solutions in various industries.
Industry Data Challenges & Indium Value Proposition
Big Data Challenges
- Complying to set regulations and adhering to privacy laws like GDPR.
- Ensure that the data is secure because of the enormous volume of data that is stored and processed.
- Managing the various sources of data is a big challenge. The volume of data produced from different sources and the velocity at which it is produced makes it difficult to manage.
- Data storage becomes an issue due to the large amounts of data pouring in. This is when data lakes and data warehouses come into use, where large chunks of data are stored. However, the challenge with storage is when the data lakes/warehouses combine data from disparate sources and this results in errors, duplicates, logic conflicts etc.
- The variety of big data technologies available makes it confusing to figure out which tool or framework will be suitable or whether a hybrid across frameworks would be required. Tech dilemmas like – Do you need Spark or will the speeds of Hadoop MapReduce be enough? – will always arise.
Big Data Value Proposition
- Obtain “real actionable insights” with the use of Big Data Analytics. These insights will be based on evidences that have passed the proof of concept stage every time they have been put to the test.
- Predictive analytics services will be able to predict outcomes even before occurrence based on analysis of past data. This will prove to be effective where corrective action needs to be taken or prevention of failure is the end game.
- Big Data can be used to discover new business opportunities. The various channels of data may prove to be new ways of interacting with your clients. Data exploration may uncover new business segments, reasons for churn and forms of churn and many other opportunities.
- Unstructured data will open a whole new world of expression. It is nothing but the expression of human language in words. NLP and text analytics can be used well here to judge the sentiments of your customers and gain visibility into your customers’ expectations.
- Broaden your views about your customers. Big data analytics will increase the magnification of analytics to a granular level. This will provide improved analytics, better customer segmentation and direct marketing.
- Move on from batch analytics and start accelerating your business into real-time operation by analyzing streaming big data.
Indium’s Perspective on Big Data Applications
The following figure illustrates the key KPIs and uses cases across Industries where Big Data applications play a key role. Indium can help build the relevant big data applications and deliver the business outcomes.