Digital transformation is reshaping the way we do business across all industries. Already today, organisations are focusing on delivering new classes of applications, such as Internet of Things (IoT), virtual reality or artificial intelligence. All of these applications have one thing in common: they require Big Data analytics. By 2020, IDC is predicting that 50 percent of the G2000 companies will see the majority of their business depend on their ability to create digitally enhanced products, services and experiences.
Big Data analytics is the heart of the digital transformation. It provides the ability to analyse data quickly and to transform it into an action plan, in order to get better insights, to take faster and more accurate decisions, and ultimately have a valuable competitive advantage.
Advanced analysis grants businesses more of an insight into any organisation and production processes, customers and markets. For a successful digital transformation journey, companies need to establish new ways of leveraging and monetising on data. For that, data analytics need to be embedded in all new apps.
It is therefore not surprising that by 2019, 40 percent of IT projects will create new digital services and revenue streams that monetise on data. Data has indeed become the new currency of the digital economy.
The need for getting better insights into one’s data is happening across all industries and verticals:
- Finance: Data analytics further improve customer experience and security to help protect and grow customers’ financial assets now and in the future.
- Hospitality sector: Data analytics improves processes and increases customer intimacy, target promotions and conduct pricing experiments.
- Manufacturing: Data insights improve security and increase product performance by streamlining the supply chain.
- Insurance sector: Firms are using analytics to underwrite policies, enabling better pricing and reshaping the companies risk portfolios.
While data analytics is the heart of the digital transformation, storage is the heart of any data analytics solution and here is why – high-performance storage ensures that analysis tools can access data quickly. A solid storage foundation is necessary for the success of any data analytics project. If the foundation is shaky, the entire performance, security and, ultimately, the success of the project, will be affected. For this reason, it is worth paying special attention to storage – right from the start.
In order to exploit data fully, users need the ability to leverage data wherever it resides and apply analytics to it. Analytics tools such as Splunk provide an open platform that can access other data stores, including Hadoop and make data in Splunk available for accessing and sharing across the organization. In order to realise top performance from Splunk—especially for ingesting and searching data fast—you require a corresponding fast, available, scalable storage platform. NetApp storage solutions for Splunk ensure that you can do faster Splunk searches while making Splunk deployment simpler, easier, and more scalable. In addition, Hadoop benefits from NetApp solutions by running jobs faster with higher throughput while using less capacity.