“If there were a single market theme in 2012 it would be that data discovery became a mainstream architecture.” (Magic Quadrant 2013) Data discovery is one of the most recent sections of data analytics and technology industry. Information is playing a very critical role in operations and processes, and users are demanding for tools that facilitate easy access, analysis and sharing of data. There has been an increased demand for business intelligence expansion, and BI vendors are continually trying to satiate these demands. However, the cost and the complexity associated with BI tools is confining the growth. Consequently, users are diverting towards a new technology which is called as “data discovery”. Data discovery tools have been gaining importance as they are both supplementary and competitive with the traditional BI tools. With advances in dashboards, search, and data analytics, these tools give more advanced and powerful applications to non-technical users, through which they can easily deploy and customize the information related to the products. Data discovery tools does not restrict, but expedite ad hoc querying, and offer more analytical flexibility to the users. There are various kinds of Data Discovery tools available, some of them are: search, dashboards, visualization, analytics, mashups etc. Definition - Search - Based Data Discovery Tools Search-based data discovery tools provide users with an ability to design views and analyze the multi-structured data using search terms. End users typically require information for taking strategic business decisions, and without knowing which computer or storage application contains the data related to their tasks, users may experience significant time delays. Se... ... middle of paper ... ...and Opportunities as Data Discovery Evolves” : Inside Analysis, Web. 09 Nov 2013. . • Sanjeev Verma: Trends in BI, “Data Discovery vs. Traditional BI Tools”, Corbus. Web. 09 Nov 2013. • “Search and Discovery Applications”, MarkLogic. Web. 19 Nov 2013. • “HP Universal Search”, HP Autonomy. Web. 20 Nov 2013 • “Advanced Search and Navigation for an Engaging User Experience”, Attivio. Web. 17 Nov 2013. . • “EasyAsk eCommerce Search”. Web. 13 Nov 2013. .
In the past number of years data has grown exponentially. This growth in data has created problems that and a race to better monitor, monetize, and organize it. Oracle is in the forefront of helping companies from different industries better handle this growing concern with data. Oracle provides analytical platforms and an architectural platform to provide solutions to companies. Furthermore, Oracle has provided software such as Oracle Business Intelligence Suite and Oracle Exalytics that have been instrumental in organizing and analyzing the phenomenon known as Big Data.
Manyika, J. (2011, May 1). Big data: The next frontier for innovation, competition, and productivity. McKinsey & Company. Retrieved May 13, 2014, from http://www.mckinsey.com/insights/business_technology/big_data_the_next_frontier_for_innovation
Traditional business intelligence tools are being replaced by data discovery software. The data discovery software has numerous capabilities that are dominating purchase requirements for larger distribution. A challenge remaining is the ability to meet the dual demands of enterprise IT and business users.
According to Lisa Arthur, big data is as powerful as a tsunami, but it’s a deluge that can be controlled. In a positive way it provides business insights and value. Big data is data that exceeds the processing capacity of conventional database systems. It is a collection of data from traditional and digital sources inside and outside a company that represents a source of ongoing discovery and analysis. The data is too big, moves to fast, or doesn’t fit the structures of the database architecture. Daily, we create 2.5 quintillion bytes of data. In the last couple years we have created 90% of data we have in the world. This data comes from many places like climate information, social media sites, pictures or videos, purchase transaction records, cell phone GPS signals, and many more places. From the beginning of recorded time through 2003 users created 5 billion gigabytes of data. 2011, the same amount was created every couple days. 2013, we created that same amount every ten minutes. Some users prefer to constrain big data into digital inputs like web behavior and social network interactions. The data doesn’t exclude traditional data that is from product transaction information, financial records and interaction channels.
The continuous growth of the business analytics software markets signifies an increase in the adoption of business analytics in business organizations. Business analytics has been crucial in optimizing organizations internally as well as maintaining flexibility to overcome unexpected external pressures as businesses shift from operating on intuition to utilizing the growing data volumes. Business analytics is defined as the processes that enable organizations to apply metrics based decision making to all business functions. Among the companies that have been successful with business analytics is Netflix, the American entertainment company. However, other companies, such as Trader Joe’s, although successful, still use the traditional intuition
For TWR, I architected and delivered scalable robust Business Intelligence platform to perform analytics on terabytes of retail data gathered from various resources incorporating convoluted security requirements.The platform was the most extensively used application by TWR executives, sales and marketing professionals
Decision making refers to the process of finding and selecting options according to the priorities and values of the person making the decision. Since there are many choices involved, it is important to identify as many options as possible so as to pick the option that best fits a company’s target, goals, values and vision. Due to the integral role of decision making in company growth and financial progress, many firms such as Amazon.com and EBay are pumping in huge investments in business intelligence systems, which are made up of certain technological tools and technological applications that are created for the purpose of facilitating improved decision making process in business. In this paper, I take a critical look at Decision Support Systems and how they affect organizational Decision making.
...g system that supports the scalability of their data. The following is their input on their new proposal to create a new operational insight tool in order to provide a solution to their challenge:
In today’s society, technology has become more advanced than the human’s mind. Companies want to make sure that their information systems stay up-to-date with the rapidly growing technology. It is very important to senior-level executives and board of directions of companies that their systems can produce the right and best information for their company to result in a greater outcome and new organizational capabilities. Big data and data analytics are one of those important factors that contribute to a successful company and their updated software and information systems.
In today’s fast paced technology, search engines have become vastly popular use for people’s daily routines. A search engine is an information retrieval system that allows someone to search the...
First of all, business intelligence analysis requires the capturing of information and storing in a single location for effective data analysis. Currently, data analysis is supported by transactional systems, business specific data marts, and other ad-hoc processes. Information is distributed making it difficult and time-consuming to access. Business teams have adapted to this environment by creating user maintained databases and manual “work-arounds” to support new types of reporting and analysis. This has resulted in inconsistent data, redundant data storage, significant resource use for maintenance, and inefficient response to changing business needs.
For the past couple of decades the majority of businesses have wanted to construct a data-driven organization or company. Furthermore, companies around the world are considering harnessing data as a basis of competitive advantage over other companies. As a result, business intelligence and data science use are popular in many organizations today. The increase in adoption of these data systems is in response to the heavy rise in communications abilities the world over. Which, in turn ,has increased the need for data products. Indeed, the Data Scientist profession is emerging to be one of the better-paying professions due to the urgent need of their labor. This paper is going to discuss what business intelligence is all about and explain data science that is usually confused to be similar to business intelligence. I will tackle a brief overview of data scientists and their role in organizations.
...ch Reips. ““Big Data”: Big Gaps of Knowledge in the Field of Internet Science.” International Journal of Internet Science 7.1 (2012): n. pag. Web. 16 Mar. 2014.
Prior to the start of the Information Age in the late 20th century, businesses had to collect data from non-automated sources. Businesses then lacked the computing resources necessary to properly analyze the data, and as a result, companies often made business d...