Harvard University called it one of the most interesting jobs of the 21st century: Today data scientists are some of the most-wanted specialists in the job market.
But they are hard to find; consulting firm McKinsey calculated that more than 150,000 positions related to data science were unfilled in 2017 in the United States alone. The banking sector, insurance businesses, IT companies or the health sector – there is hardly any business area which is not in the need of skilled workers analyzing newly tapped data streams.
Big Data is challenging companies around the globe. Building up and generating data sources is one thing; harvesting data sets for usual and unusual patterns or precise predictions of production outcomes is another.
“Data is the new oil” has been the slogan for many years. But just as with real-world offline oil – data can be useless if it is not refined. And that’s where data scientists enter the stage. They connect, decrypt and analyze gathered data and try to create a coherent story – and business cases – out of it. No CIO – or CDO – is able to improve its company processes if he doesn’t know the potential of the data generated through his/her IT infrastructure.
Businesses can gain valuable insights by using data mining: They understand how users interact with the product, or at what time fault signals are likely to appear in their productions lines. They discover real competitive advantages compared to other market players. Obsessive customer focus is driving innovation and collaboration around products, services and payments. Supply chains have to deliver smaller quantities with shorter lead times and lower costs. Production is aligning with consumption – and becoming more flexible and more efficient in the process. Data scientists work at the pulse of these challenges and deliver solutions to make the most of process optimization.
Artificial intelligence (AI), machine learning and predictive analytics will define the next generation of software. Data scientists will take a crucial role in shaping these technologies within companies worldwide.
But with the current drought of them, how can businesses progress? With Zementis, Software AG has acquired cutting-edge machine learning technology to establish a common, standards-based framework to deliver intelligent solutions across all industries and applications. Using Zementis, organizations can harness the power of their data to rapidly deliver insights and support informed business decisions based on predictive analytics tools. And data scientists can exchange predictive models between different applications and vendors and implement a wide range of machine learning and predictive algorithms.
Digitalization is in full swing, and the increase in efficiency can be game-changing. Data scientists can enrich your data picture and leverage more accurate predictive models by analyzing huge data sets, often in real-time. The race to gain data sovereignty demands a fast pace of innovation, especially within your company.Success is no longer about changing strategies more often, but having the agility to execute your data strategy concurrently. Data scientists can help, along with Zementis.