Look back and you will see Statistics as an old field of study that has evolved over time. Procuring data, processing it and analyzing market trends have been there for a while. However, as with all the things that have been for a while, statistics is not untouched by the technology boom. Data Science, the term first came up in 1996 at International Federation of Classification Societies. Since then this field has influenced fraud and risk assessment, land management, market assessment, economics, and commerce to name a few.
Data science adds the concoction of Big Data to statistics to create an analytical framework that is efficient and accurate in predictions. It has the potentiality to not just influence, but change the way business analytics, decision making, risk assessment, strategy creation functions.
A Future of Great Expectations
With its ever-increasing field of application, data science is here to stay. When you look at the overall data generated till date, 90% of it is from the last two years. If you want to have an idea about the amount of data that is generated in the current scenario, its 2.5 quintillion bytes per day.
Every post, text, and search generates data. For example, Google alone executes 3,607,080 searches every minute, people send 15,220,700 texts via various platforms per minute, now add to it social media posts and updates, that is a big data with bigger analytical potential.
Organizations are realizing the importance of Big Data across domains. It is not just about the start-ups or young organizations opting for data science, but many traditional business giants are putting their foot into this vast field.
Startups, use data analysis as a tool to create innovative disruption, create demand for their product or concept. Data science for them is not just a vertical, but an integral part of their core machinery. Traditional organizations invest in data science to add accuracy in understanding market trends, risk analysis to create strategies.
AT&T implemented data science in customer experience in understanding the complex flow chart of problem and solution. Data science enabled a simple solution to the complex permutation and combination of many problems and enhanced efficiency by many folds.
Challenges in Hand
The biggest challenge as per Murli Buluswar, Chief Science Officer at GE is to evolve from a heuristics based ‘knowing culture’ to a data-enabled ‘learning culture’. There is a fear game involved when it comes to a thinking evolution that shifts to dynamic data based learning.
Ruben Sigala, the Chief Analytics Officer at Caesars Entertainment says the main challenge they face is to enable a set of tools that add value to the process by creating an integrated ecosystem.
Data privacy; what to share and what not to share, is a challenge as per Zoher Karu, VP, Global Customer Optimization and Data at eBay. Providing customers with a return value for the data minimizes complexities in this area to a greater extent.
What can Data Scientists Expect Moving Forward?
When you take into consideration the immense potential of data science with its challenges it becomes evident that organizations are looking for certified professionals who not just understand the technical know-how, but also adds value to the process by creating an integrated ecosystem. When you look at the current career opportunities for Data Scientists, the graph is upward bound.
- As per a report published by LinkedIn, Data Scientists, Machine Learning, and Big Data Professionals are one of the fastest growing jobs.
- If you go by Forbes there have been more than 650% rise in Data Scientist jobs since 2012.
- With a steady rise in the use of social media and other platforms requirement of the right talent will be on rising.
- US alone just has 35,000 professionals and the requirement sure is high.
- Companies like AIG and AT&T are looking for someone with a skill set match of 60-75% so that they can grow at work and they acknowledge a crunch of the right talent
Data science has an immense potential to add value to a company process if led in a focus driven strategy.
The Future Evolution
Ruben Sigala, the Chief Analytics Officer at Caesars Entertainment stresses on having a very specific vision regarding how data science is intended to influence functions within the organization and its interaction with the business market. Some companies may have their focus on internal traditional verticals like sales, marketing, finance, pricing to implement data science. Other organizations may have a broader perspective.
The Chief Information Officer at GE Software stresses on an outcome-based approach, where the focus is on the result and data science is aligned to achieve the result.
Going by the example of American Express, focus on improving data quality brings a great return on investment.
If we go by these future trends, it is an exciting time to be a data scientist:
- Data Scientists will be expected to be specialists, who can create an integrated ecosystem in association with analysts, line managers.
- The organizations that plan to implement a broad and all-inclusive application will require Data Scientists, who can oversee the entire data cycle.
- Data Scientists need to have an expertise in fishing the most relevant data from the big sea of data in hand
- Simplification is the mantra for data scientists as it adds value across verticals. They need to keep themselves updated with the most intuitive platforms that make data easy to interpret.
Organizations all across are looking for the right talent in data science that will enable them to achieve a value based ecosystem. Take the example of eBay, where the preference is for someone with the cross-functional skill set as Data Science becomes integrated with other departments.
You may start with a specific skill set, but moving forward adding more certifications and cross-functional credentials to your name will be a wise move in a sector that is growing and dynamic.
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