Database Trends That Will Take The Spotlight This Year

There is sudden increase in the way data is currently being collected. People use smart phones and smart tablets and connected to internet throughout the day. Most of the shopping has gone online. As a result, data is getting collected in different formats and from different applications. The rapid expansion of Big Data is further fueled by exponential increase in usage of internet and people ability to interact on social media and different networking applications including YouTube, Gmail, Facebook to name a few. But just how easy is the task to leverage the vast amount of data, which is called Big Data, our computer systems are collecting on a daily basis? What significant challenges are currently faced by the organizations

2015, what a year to be in business or politics. A year full of unbelievable change across America. Equally, what a year to be a consumer or constituent, being a recipient of new innovation, economic shifts, and laws. As well engage in topics that have caused frustration, anger, along with excitement.

As the company yearns to adopt advanced analytics with the focus of predictive analytics, it needed a new, modern architecture and innovative technologies to support it. The process and journey led to the adoption of in-database and in-memory processing. It has been several years of evaluating and exploring different technologies and vendors.

I did this research by reading scientific literatures. I started with the NMC Horizon Reports, from which I quoted some important trends mentioned in it, for example Cloud computing, wearable technology, etc., and got some

Data has always been analyzed within companies and used to help benefit the future of businesses. However, the evolution of how the data stored, combined, analyzed and used to predict the pattern and tendencies of consumers has evolved as technology has seen numerous advancements throughout the past century. In the 1900s databases began as “computer hard disks” and in 1965, after many other discoveries including voice recognition, “the US Government plans the world’s first data center to store 742 million tax returns and 175 million sets of fingerprints on magnetic tape.” The evolution of data and how it evolved into forming large databases continues in 1991 when the internet began to pop up and “digital storage became more cost effective than paper. And with the constant increase of the data supplied digitally, Hadoop was created in 2005 and from that point forward there was “14.7 Exabytes of new information are produced this year" and this number is rapidly increasing with a lot of mobile devices the people in our society have today (Marr). The evolution of the internet and then the expansion of the number of mobile devices society has access to today led data to evolve and companies now need large central Database management systems in order to run an efficient and a successful business.

The fundamental challenge was the heterogeneity of scientific disciplines and technologies that needed to cooperate to accomplish this goal, and the necessity of getting all stakeholders to cooperate in its development. A compounding factor is that while technology evolves rapidly, people’s habits, work practices, cultural attitudes towards data sharing, and willingness to use other’s data, all evolve more slowly. How the relationship of people to the infrastructure evolves determines whether it succeeds or fails.

Visionary executives are finding opportunities beyond existing and traditional data repositories, such as on-premises CRM and ERP systems. Today 's data can include social media posts, customer journey information, Internet of things (IoT) data, and more.

Data and information management is a huge growth area. But it's not just data management creating new job opportunities, its gathering, analyzing, storing and securing the data as well.

Apache Hadoop is an open source framework and its helps in the distributed processing of

My broad research interest is in creating new systems that seek to revolutionize industry workflows. It has been my experience that solving industry problems by building next-generation systems exposes the most challenging and rewarding research areas. My passion for tackling such problems drew me towards Information Management and Analytics. Data generation is accelerating. It is physically impossible for individuals to analyze data created every second to extract important details. This trend of “Big Data” is not slowing down -- on the contrary, as industries automate and digitize, data generation is going to explode. This is already fueling demand for versatility in automated analysis of sales trends, user behavior, and other information. This surge in demand is exposing incredible research problems that I am craving to work on, especially where distributed systems meets information management. Some of the biggest problems I have tackled during my undergraduate years have been in systems research; I want to continue down this path during my graduate studies by working on next-generation systems and protocols that address the industry’s biggest information management challenges.

Current Information and Communication technology includes big data, the cloud, mobile communication, and social media. These ICT developments marked latest trends in ICT, and promise to bring enormous potential improvement in ICT industry in future. These developments will further pass to a whole range of industries and sectors that leverage ICT.

Nowadays, it seems that almost anything and everything is available online at any time. You can check email from your phone, find friends, order food, and even manage employees. Apps these days are producing extraordinary amounts of data from a wide array of sources. With such a large volume of data being passed online, it was only a matter of time before companies would want to analyze this raw data to better understand and improve the day to day operations and functions. Companies like Google can use your browsing data to target advertising (Google, n.d.) and help improve functionality of their proprietary apps like Google Maps (Mehta, 2016). Hospitals use clinical based data to study patient trends, which gives a better insight into

The volume of stored data will enable the analysis of Big Data and the determination of Business Intelligence (BI) appropriate to each demand in each of the participating countries.

“It is common for the shallow and deep sections of a real swimming pool to be connected by a gradual slope. However, too often this sloped section is missing when it comes to how data is shared at companies. The data is only available in two depths – one for the data novice (1.5 feet) and one for the data scientist (30 feet) with a steep drop-off between the levels. As interest in data continues to grow, it is critical to create a better bridge between these depths. Organizations are discovering there’s a wider group of business users who need to explore the data more freely and deeply on their own. Like my twins, they’re eager to venture beyond the shallow end but may not be prepared to swim on their own in the deep end.” (Dykes, The age of data democratization: How to effectively share data across your business | Bloomberg, 2015)

Current potential customer: Currently In-memory technology is more suitable for small or medium enterprise (Haji, 2011). This is due to price of memory.