The digital transformation (DT) of enterprises is enabled by the judicious use of Big Data. And it’s open source technologies that are the driving force behind the power of Big Data and DT.
Digital Transformation (DT) and Big Data combine to offer several advantages. Big Data based digitally transformed systems make life easier and smarter, whether in the field of home automation or industrial automation. The digital world tracks Big Data generated by IoT devices, etc. It tries to make this data more productive and hence, DT should be taken for granted as the world progresses.
For example, NASA ‘s rover ‘Curiosity’ is sending Big Data from Mars to the Earth. As compared to data sent by NASA’s satellites that are revolving around Mars, this data is nothing but digitally transformed Big Data, which works with DT to provide a unique platform for open source applications. Today, ‘Curiosity’ has its own Twitter account with four million followers.
A Digital Transformation isn’t complete unless a business adopts Big Data. The phrase “Data is the new crude oil,” is not new. However, crude oil itself has no value, unless it is refined into petrol, diesel, tar, wax, etc. Similarly, in our daily lives, we deal with tons of data. If this data is refined to a useful form, only then is it of some real use.
As an example, we can see the transformation televisions have undergone, in appearance. We once had picture tube based TVs. Today, we have LEDs, OLEDs, LCD based TVs, curved TVs, Internet enabled TVs, and so on. Such transformation is also quite evident in the digital world.
In a hospital, several patients may be diagnosed with cancer, each year. The patient data generated is voluminous, including treatment methods, diverse drug therapies, patient responses, genetic histories, etc. But such vast pools of information, i.e., Big Data, would serve no useful purpose without proper analysis. So DT, coupled with Big Data and open source applications, can create a more patient-focused and effective treatment – one that might have higher recovery rates.
Big Data combines structured data with unstructured data to give us new business insights that we’ve never had before. Structured data may be traditional spreadsheets, your customer list, information about your products and business processes, etc. Unstructured data may include Google Trends data, feeds from IoT sensors, etc. When a layer of unstructured data is placed on top of structured data and analysed, that’s where the magic happens.
Let’s look into a typical business situation. Let’s suppose a century old car-making company asks its data team to use Big Data concepts to find an efficient way to make safe sales forecasts. In the past, the team would look at the number of products it had sold in the previous month, as well as the number of cars it had sold a year ago and use that data to make a safe forecast. But now the Big Data teams use sentiment analysis on Twitter and look at what people are saying about its products and brand. They also look at Google Trends to see which similar products and brands are being searched the most. Then they correlate such data from the preceding few months with the actual current sales figures to check if the former was predictive – i.e., had Google Trends over the past few months actually predicted the firm’s current sales figures?
In the case of the car company, while making sales forecasts, the team used structured data (how many cars sold last month, a year ago, etc) and layers of unstructured data (sentiment analysis from Twitter and Google Trends) and it resulted in a smart forecast. Thus, Big Data is today becoming more effective in business situations like sales planning, promotions, market campaigns, etc.
Open source is the key to DT
Open source, nowadays, clearly dominates domains like Big Data, mobile and cloud platforms. Once open source becomes a key component that delivers a good financial performance, the momentum is unstoppable. Open source (often coupled with the cloud) is giving Big Data based companies like Google, Facebook and other Web giants flexibility to innovate faster.
Big Data companies are using DT to understand their processes, so that they can employ technologies like IoT, Big Data analytics, AI, etc, better. The journey of enterprises migrating from old digital infrastructure to new platforms is an exciting trend in the open source environment.
Organisations are relying on data warehouses and business intelligence applications to help make important data driven business decisions. Different types of data, such as audio, video or unstructured data, is organised in formats to help identify it for making future decisions.
Open source tools used in DT
Several open source tools are becoming popular for dealing with Big Data and DT. Some of them are listed below.
- Hadoop is known for the ability to process extremely large data volumes in both structured and unstructured formats, reliably placing Big Data to nodes in the group and making it available locally on the processing machine.
- MapReduce happens to be a crucial component of Hadoop. It works rapidly to process vast amounts of data in parallel on large clusters of computer nodes. It was originally developed by Google.
- Storm is different from other tools with its distributed, real-time, fault-tolerant processing system, unlike the batch processing of Hadoop. It is fast and highly scalable. It is now owned by Twitter.
- Apache Cassandra is used by many organisations with large, active data sets, including Netflix, Twitter, Urban Airship, Cisco and Digg. Originally developed by Facebook, it is now managed by the Apache Foundation.
- Kaggle is the world’s largest Big Data community. It helps organisations and researchers to post their data and statistics. It is an open source Big Data tool that allows programmers to analyse large data sets on Hadoop. It helps with querying and managing large data sets really fast.
DT: A new innovation
DT is the result of IT innovation. It is driven by well-planned business strategies, with the goal of inventing new business models. Today, any organisation can undergo business transformation because of three main business-focused essentials — intelligence, the ability to decide more quickly and a customer-centric outlook.
DT, which includes establishing Big Data analytics capabilities, poses considerable challenges for traditional manufacturing organisations, such as car companies. The successful introduction of Big Data analytics often requires substantial organisational transformation including new organisational structures and business processes.
Retail is one of the most active sectors when it comes to DT. JLab is an innovative DT venture by retail giant John Lewis, which offers lots of creativity and entrepreneurial dynamism. It is even encouraging five startups each year and helps them to bring their technologies to market. For example, Digital Bridge, a startup promoted by JLab, has developed a clever e-commerce website that allows shoppers to snap photos of their rooms and see what furniture and other products would look like in their own homes. It automatically detects walls and floors, and creates a photo realistic virtual representation of the customer’s room. Here, lighting and decoration can be changed and products can be placed, rotated and repositioned with a realistic perspective.
Companies across the globe are going through digital business transformation as it helps to improve their business processes and leads to new business opportunities. The importance of Big Data in the business world can’t be ignored. Nowadays, it is a key factor for success. There is a huge amount of valuable data which companies can use to improve their results and strategies. Today, every important decision can and should be supported by the application of data analytics.
Big Data and open source help DT do more for businesses. DT helps companies become digitally mature and gain a solid presence on the Internet. It helps companies to identify any drawbacks that may exist in their e-commerce system.
Big Data in DT
Data is critical, but it can’t be used as a replacement for creativity. In other words, DT is not all about creativity versus data, but it’s about creativity enhanced by data.
Companies gather data to analyse and improve the customer experience, and then to create targeted messages emphasising the brand promise. But emotion, story-telling and human connections remain as essential as ever. The DT world today is dominated by Big Data. This is inevitable given the fact that business organisations always want DT based Big Data, so that data is innovative, appealing, useful to attract customers and hence to increase their sales.
Tesla cars today are equipped with sensors and IoT connections to gather a vast amount of data. Improvements based on this data are then fed back into the cars, creating a better driving experience.
DT in India
DT can transform businesses across every vertical in India. Data analytics has changed from being a good-to-have to a must-have technology.
According to a survey by Microsoft in partnership with International Data Corporation (IDC), by 2021, DT will add an estimated US$ 154 billion to India’s GDP and increase the growth rate by 1 per cent annually. Ninety per cent of Indian organisations are in the midst of their DT journey. India is the biggest user and contributor to open source technology. DT has created a new ripple across the whole of India and is one of the major drivers for the growth of open source. The government of India has encouraged the adoption of this new technology in the Digital India initiative, and this has further encouraged the CEOs of enterprises and other government organisations to make a move towards this technology.
The continuous DT in India is being driven faster with the adoption of emerging technologies like Big Data. That’s one of the reasons why organisations today are investing in these technological capabilities. Businesses in India are recognising the challenges of DT and embracing them. Overall, it may be said that the new DT concept is more investor and technology friendly, in tune with the ‘Make in India’ programme of the present government.
From finding ways to increase business efficiency and trimming costs, to retaining high-value customers, determining new revenue opportunities and preventing fraud, advanced analytics is playing an important role in the DT of Big Data based companies.
The way forward
Access to Big Data has changed the game for small and large businesses alike. Big Data can help businesses to solve almost every problem. DT helps companies to embrace a culture of change and remain competitive in a global environment. Losing weight is a life style change and so is the incorporation of Big Data into business strategies.
Big Data is the currency of tomorrow, and today, it is the fuel running a business. DT can harness it to a greater level.
The author is a B.E. in industrial production, and has been a lecturer in the mechanical engineering department for ten years at three different polytechnics. He is also a freelance writer and cartoonist. He can be contacted at email@example.com or firstname.lastname@example.org.