This research note is restricted to the personal use of tjean-louis@gatech.edu G00263047 Answering Big Data's 10 Biggest Vision and Strategy Questions Published: 12 August 2014 Analyst(s): Douglas Laney, Alexander Linden, Frank Buytendijk, Andrew White, Mark A. Beyer, Neil Chandler, Jenny Sussin, Nick Heudecker, Merv Adrian Gartner analysts address the most pressing vision and strategy questions that business, analytics and information professionals have, providing valuable insights on dealing with big data projects successfully. Key Challenges ■ Even as organizations are embarking on big data initiatives, many still have several vision and strategy questions regarding how to drive the most value from these vital projects. ■ As …show more content…
Whether your organization is just embarking on a big data initiative, or if you are further along the maturity curve and looking to take the next step in deriving value, Gartner can provide support and guidance. In this piece, Gartner analysts address the most pressing and prevalent questions they receive about big data vision and strategy. (For further information, read our companion piece on the biggest planning and implementation big data questions, "Answering Big Data's 10 Biggest Planning and Implementation Questions.") In this note, we tackle both the hype and practical matters surrounding big data, including questions such as: ■ Is there actually any real substance behind all these big data discussions? ■ How do you know what data can be used and what potential usage might attract public criticism? Page 2 of 11 Gartner, Inc. | G00263047 This research note is restricted to the personal use of tjean-louis@gatech.edu This research note is restricted to the personal use of tjean-louis@gatech.edu ■ What is the value of big data projects? ■ Where is this value found and how can it be justified and proven to the rest of the organization? ■ What sources should you gather information from, how can you collect social media and what are other leading organizations doing with big data? Finally, we look at the issue of your big data organization and skills: ■ What skills are required for big data? ■ Is there a difference between a data
Brown, B., Chiu, M., Manyika, J. (2011), Are you ready for the era of big data? Retrieved
Big Data is the act of compiling large sets of data based on a single individual or groups. Everyone encounters data in their daily life--you are experiencing it when you log onto a social media account, when you stream entertainment online, or even when you are online shopping. When you do any of these things you are leaving behind a digital trace that can be accessed by just about anyone. In “Six Provocations for Big Data,” danah boyd and Kate Crawford raise questions regarding the nature of Big Data. What is considered public information? What is the ethical way to go about retrieving data from online sources? Is Big Data more harmful or helpful? How often do you encounter Big Data, or data in general? What is the relationship between data
Through informational interviews with seven industry experts and a thorough literature review, the team explored the concept of “big data” and generated key insights which will guide the Federation’s approach as the organization develops its members’ data analytics capacities. Additionally, the team identified a clear business case for implementing data analytics at CDCUs using strategies appropriate for the level of resources within each individual organization. The team also developed a set of survey questions for the client to use when gauging the level of interest and capacity within any individual CDCU.
Since the 1970’s databases and report generators have been used to aid business decisions. In the 1990’s technology in this area improved. Now technology such as Hadoop has gone another step with the ability to store and process the data within the same system which sparked new buzz about “big data”. Big Data is roughly the collection of large amounts of data – sourced internally or externally - applied as a tool – stored, managed, and analyzed - for an organization to set or meet certain goals.
Every day, we produce 2.5 quintillion bytes of data. 90% of all data in the world was produced in the past two years. Data has been around forever; we have always gathered information. Paleolithic cavemen recorded their activities by carving them in stone or notching them in sticks. Egyptians used hieroglyphics to record significant events in history. The Library of Alexandria was home to half-a-million scrolls of the ancient world. Less than hundred years ago, we used punch cards to record and store information. As technology continues to evolve, the amount of data we store continues to grow. We’ve come a long way since stone tablets, scrolls, and punch cards. It’s important to understand the concept of big data and the impact is has created. This paper will define the classifications of data, explain the challenges of big data, and describe how big data analytics is being used in today’s data driven world.
Big data and its definition has changed over the years. In a 2011 research project by MGI and Mckinsey’s Business’ defined big data as
Today, data is a growing asset that various businesses are having difficulty converting into a powerful strategic tool. Companies need help turning this data into valuable insight, which can diminish risk and enhance returns on investments. Companies are struggling to make sense and obtain value from their big data. Superior and reliable
With big data seeming to boom so fast, it 's not surprising that problems in the processing of these enormous data sets were overlooked. With something so popular still in the experimental phase, there is a multitude of troubles that arise from the lack of rules or guides to limit how researchers manipulate the data in order to pull out the correlations that many big data scientists discover.
Big data and analytics are hot growth areas, not only for IT organizations, but for businesses across all industries.
Qualified professionals that are able work on new technologies and to interpret data are limited. “Big Data” is a relatively new concept, consequently, there is a shortage of experts that can interpret the information of a business like Peter Mayer’s to get understanding of what the agency’s needs are.
Business thrive when they have the most accurate, up-to-date, and relevant information at their disposal. This information can be used for a plethora of pertinent markers in small and large businesses, relating to accounting, investments, consumer activity, and much more. Big data is a term used to describe the extremely large amounts of data that floods a business every day. For decades, big data has been a growing field, facing controversy on many levels, but as of late, it has been a major innovator in the challenge of making businesses more sustainable. Big data is often scrutinized for its over-generalization and inability to display meaningful results at times. When applied correctly, data analysis can bring earth-altering information to the table.
Presence of big data is a very common phenomenon now days, specially when talking about medium to large size corporation. Manyika et al., in their article (James Manyika, 2011) defined the term big data as “large pools of data that can be captured, communicated, aggregated, stored, and analyzed”. To clarify they suggested that big data refers to data, whose size makes it impossible to be processed by the typical software used for database management. Gartner (Gartner, 2012)defined big data in terms of its characteristics of high volume, high velocity and high variety. By volume, he referred to the size of the data, by velocity he referred to the speed at which the data is created and by variety he referred to the range of types of data.
Data is the most valuable tool in your business. Based on a Gartner survey, 73% of organizations have invested or plan to invest in big data within the next two years.
big data is a dynamic that seemed to appear from almost nowhere. But in reality, Big Data is not new – and it is moving into mainstream and getting a lot more attention. the growth of Big Data is being enabled by inexpensive storage, a proliferation of sensor and data capture technology, increasing connections to information via the cloud and virtualised storage infrastructure, as well as innovative software and analysis tools. It is no surprise then that business analytics as a technology area is rising on the radars of CiOs and line-of-business (lOB) executives. to validate this, as part of a recent survey of 5,722 end users in the uS market, business analytics ranked in the top five It initiatives of organisations. the key drivers for business analytics adoption remained conservative or defensive. the focus on cost control, customer retention and optimising operations is likely a reflection of the continued economic uncertainty. however,
Big Data is one of the most discussed concepts in the business world today. The concept of Big Data is one that has been increasingly debated over the past few years by many different kinds of business industries. One industry where this discussion is prominent is the accounting profession. Big Data will be defined more in-depth later on, but in shorter terms, Big Data refers to the exponential sum of data available in our world today. This amount of data is beyond the traditional analysis that can be computed by human power. When Big Data is converted and used to its full potential, it could have a material impact on the accounting industry as we know it. Companies today must stay on top of the Big Data trend if they wish to