Suraj Pai, Vice President for Database & Technology, SAP Southeast Asia.
Most companies realise that to gain a competitive advantage is to obtain better data, interpret them quickly, and distribute them in easier-to-use formats. But there are many obstacles to the effective use of data, resulting in unused corporate data in many companies. As companies grow in revenue and volume, they churn out a huge volume of transactional data usually in mega- and terabytes of customer, partner and operational information.
All this corporate wealth of information can either be stored for future use or be analysed immediately and applied into existing information management processes. Either way, the volume of data being created can have a massive, negative effect on how it needs to be utilised or maintained by the company's decision makers. The questions often asked among executives are: "How can I get access to my sales data now?", "How are we going to keep up with this much volume of data?" "How are we going to use it for our operations?" Perhaps the most difficult question to answer is: "How much will it cost us to use this data?"
Times are gradually changing in the world of business analytics. Traditional methods of data management are being challenged given the volume, variety and velocity of data pouring in from employees, customers, partners, etc., through a variety of sources like enterprise systems, social media sites, smartphones, tablets and other consumer devices including PCs and laptops. Keeping track of all these file types, where they go, and how to use them is a very daunting task especially for companies that are data-intensive, such as those in the power sector, financial services, telecom, food & beverage, and even information technology.
In recent years, development in in-memory database has put forth some novel but very promising functions that revolutionise database management systems. By definition, in-memory database refers to a database management system that utilises main memory (RAM) of a computing infrastructure to store data. Compared to traditional disk storage processes, in-memory database is immediately captured and processed or analysed in real-time, thus reducing the need to wait for certain results to be received by the user.
In-Memory Database as a Game Changer
Why is in-memory database important when processing big data? It's simply because in-memory database cuts down the entire process of analysing data that may be important the moment it's received. In addition, by having an in-memory database process, company executives can start reviewing other types of data that they never thought they had. In which case, they could either improve their overall business operations or create new services, or even both.
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