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Big Data(Mckinsey Report)

1. 1. Report on: Big data The next frontier for innovation, competition, and productivity.

2. 2. What do we mean by "big data"? * Big Data is also data but with a huge size. Big Data is a term used to describe a collection of data that is huge in size and yet growing exponentially with time. In short such data is so large and complex that none of the traditional data management tools are able to store it or process it efficiently. * It also refers to datasets whose size is beyond the ability of typical database software tools to capture, store, manage, and analyze. This definition is intentionally subjective and incorporates a moving definition of how big a dataset needs to be in order to be considered big data i.e. We don't define big data in terms of being larger than a certain number of terabytes (thousands of gigabytes). We assume that, as technology advances over time, the size of datasets that qualify as big data will also increase. Also note that the definition can vary by sector, depending on what kinds of software tools are commonly available and what sizes of datasets are common in a particular industry. With those caveats, big data in many sectors today will range from a few dozen terabytes to multiple petabytes (thousands of terabytes).

3. 3. Big Data * The amount of data in our world has been exploding. Companies capture trillions of bytes of information about their customers, suppliers, and operations, and millions of networked sensors are being embedded in the physical world in devices such as mobile phones and automobiles, sensing, creating, and communicating data. * Multimedia and individuals with smartphones and on social network sites will continue to fuel exponential growth. Big data-large pools of data that can be captured, communicated, aggregated, stored, and analyzed-is now part of every sector and function of the global economy. Like other essential factors of production such as hard assets and human capital, it is increasingly the case that much of modern economic activity, innovation, and growth simply couldn't take place without data.

4. 4. History and evolution of big data analytics * The concept of big data has been around for years; most organizations now understand that if they capture all the data that streams into their businesses, they can apply analytics and get significant value from it. But even in the 1950s, decades before anyone uttered the term "big data," businesses were using basic analytics (essentially numbers in a spreadsheet that were manually examined) to uncover insights and trends.

5. 5. Mapping global data: Growth and value creation * Many of the most powerful inventions throughout human history, from language to the modern computer, were those that enabled people to better generate, capture, and consume data and information. We have witnessed explosive growth in the amount of data in our world. Big data has reached critical mass in every sector and function of the typical economy, and the rapid development and diffusion of digital information technologies have intensified its growth. * Many consumers are suspicious about the amount of data that is collected about every aspect of their lives, from how they shop to how healthy they are. Is big data simply a sign of how intrusive society has become, or can big data, in fact, play a useful role in economic terms that can benefit all societal.

6. 6. Measuring data * Measuring volumes of data provokes a number of methodological questions. First, how can we distinguish data from information and from insight? Common definitions describe data as being raw indicators, information as the meaningful interpretation of those signals, and insight as an actionable piece of knowledge. For the purposes of sizing big data in this research, we focused primarily on data sized in terms of bytes. But a second question then arises. When using bytes, what types of encoding should we use? In other words, what is the amount of assumed compression in the encoding?

7. 7. Why is big data analytics important? * Big data analytics helps organizations harness their data and use it to identify new opportunities. That, in turn, leads to smarter business moves, more efficient operations, higher profits and happier customers. * Cost reduction. Big data technologies such as Hadoop and cloud- based analytics bring significant cost advantages when it comes to storing large amounts of data - plus they can identify more efficient ways of doing business.

8. 8. Conti.... * Faster, better decision making. With the speed of Hadoop and in-memory analytics, combined with the ability to analyze new sources of data, businesses are able to analyze information immediately - and make decisions based on what they've learned. * New products and services. With the ability to gauge customer needs and satisfaction through analytics comes the power to give customers what they want. Davenport points out that with big data analytics, more companies are creating new products to meet customers' needs. * Time Reduction-If we know what customers are purchasing or what feedback customer gave, it will be easy for organization to analyze their customer needs even time can be saved.

9. 9. Types Of Big Data * Structured: Any data that can be stored, accessed and processed in the form of fixed format is termed as a 'structured' data. Over the period of time, talent in computer science has achieved greater success in developing techniques for working with such kind of data (where the format is well known in advance) and also deriving value out of it. However, nowadays, we are foreseeing issues when a size of such data grows to a huge extent, typical sizes are being in the rage of multiple zettabytes.

10. 10. Conti... * Unstructured: Any data with unknown form or the structure is classified as unstructured data. In addition to the size being huge, un-structured data poses multiple challenges in terms of its processing for deriving value out of it. A typical example of unstructured data is a heterogeneous data source containing a combination of simple text files, images, videos etc. Now day organizations have wealth of data available with them but unfortunately, they don't know how to derive value out of it since this data is in its raw form or unstructured format. * Semi-structured: Semi-structured data can contain both the forms of data. We can see semi-structured data as a structured in form but it is actually not defined with e.g. a table definition in relational DBMS. Example of semi-structured data is a data represented in an XML file.

11. 11. Examples Of Big Data * The New York Stock Exchange generates about one terabyte of new trade data per day. * The statistic shows that 500+terabytes of new data get ingested into the databases of social media site Facebook, every day. This data is mainly generated in terms of photo and video uploads, message exchanges, putting comments etc.

12. 12. 1. DATA HAVE SWEPT INTO EVERY INDUSTRY AND BUSINESS FUNCTION AND ARE NOW AN IMPORTANT FACTOR OF PRODUCTION * Several research teams have studied the total amount of data generated, stored, and consumed in the world. * Big data has now reached every sector in the global economy. Like other essential factors of production such as hard assets and human capital, much of modern economic activity simply couldn't take place without it. * The most potential to create value through the use of big data will be in the most developed economies. Looking ahead, however, there is huge potential to leverage big data in developing economies as long as the right conditions are in place. * The possibilities of big data continue to evolve rapidly, driven by innovation in the underlying technologies, platforms, and analytic capabilities for handling data, as well as the evolution of behavior among its users as more and more individuals live digital lives.

13. 13. 2. BIG DATA CREATES VALUE IN SEVERAL WAYS * Creating transparency :Simply making big data more easily accessible to relevant stakeholders in a timely manner can create tremendous value. * Enabling experimentation to discover needs, expose variability, and improve performance: As they create and store more transactional data in digital form, organizations can collect more accurate and detailed performance data * Segmenting populations to customize actions: Big data allows organizations to create highly specific segmentations and to tailor products and services precisely to meet those needs. * Replacing/supporting human decision making with automated algorithms: Sophisticated analytics can substantially improve decision making, minimize risks, and unearth valuable insights that would otherwise remain hidden. Such analytics have applications for organizations.

14. 14. 3.USE OF BIG DATA WILL BECOME A KEY BASIS OF COMPETITION AND GROWTH FOR INDIVIDUAL FIRMS * The use of big data is becoming a key way for leading companies to outperform their peers. For example, we estimate that a retailer embracing big data has the potential to increase its operating. * This effort will take time, but the impact of developing a superior capacity to take advantage of big data will confer enhanced competitive advantage over the long term and is therefore well worth the investment to create this capability. But the converse is also true. In a big data world, a competitor that fails to sufficiently develop its capabilities will be left behind. * Big data will also help to create new growth opportunities and entirely new categories of companies, such as those that aggregate and analyze industry data. Many of these will be companies that sit in the middle of large information flows where data about products and services, buyers and suppliers, and consumer preferences and intent can be captured and analyzed

15. 15. 4. THE USE OF BIG DATA WILL UNDERPIN NEW WAVES OF PRODUCTIVITY GROWTH AND CONSUMER SURPLUS * The opportunities have the potential to improve efficiency and effectiveness, enabling organizations both to do more with less and to produce higher-quality outputs, i.e,increase the value-added content of products and services. * An example is a mobile phone that has learned its owner's habits and preferences, that holds applications and data tailored to that particular user's needs, and that will therefore be more valuable than a new device that is not customized to a user's needs.

16. 16. THERE WILL BE A SHORTAGE OF TALENT NECESSARY FOR ORGANIZATIONS TO TAKE ADVANTAGE OF BIG DATA * A significant constraint on realizing value from big data will be a shortage of talent, particularly of people with deep expertise in statistics and machine learning, and the managers and analysts who know how to operate companies by using insights from big data. * we expect big data to rapidly become a key determinant of competition across sectors. But we project that demand for deep analytical positions in a big data world could exceed the supply being produced on current trends. * It is necessary to retrain a significant amount of the talent in place; fortunately, this level of training does not require years of dedicated study.

17. 17. SEVERAL ISSUES WILL HAVE TO BE ADDRESSED TO CAPTURE THE FULL POTENTIAL OF BIG DATA * Data policies: As an ever larger amount of data is digitized and travels across organizational boundaries, there is a set of policy issues that will become increasingly important, including, but not limited to, privacy, security, intellectual property, and liability. * Technology and techniques: To capture value from big data, organizations will have to deploy new technologies (e.g., storage, computing, and analytical software) and techniques (i.e., new types of analyses). There is also a need for ongoing innovation in technologies and techniques that will help individuals and organizations to integrate, analyze, visualize, and consume the growing torrent of big data. * Organizational change and talent: Organizational leaders often lack the understanding of the value in big data as well as how to unlock this value. In addition, many organizations today do not structure workflows and incentives in ways that optimize the use of big data to make better decisions and take more informed action.

18. 18. Conti.... * Access to data: To enable transformative opportunities, companies will increasingly need to integrate information from multiple data sources. In some cases, organizations will be able to purchase access to the data.Other stakeholders must find ways to offer compelling value propositions to holders of valuable data. * Industry structure: Sectors with a relative lack of competitive intensity and performance transparency, along with industries where profit pools are highly concentrated, are likely to be slow to fully leverage the benefits of big data. Organization leaders and policy makers will have to consider how industry structures could evolve in a big data world if they are to determine how to optimize value creation at the level of individual firms, sectors, and economies as a whole.

19. 19. To improve service levels even further, public cloud providers offer big data capabilities through managed services that include: * Apache Hadoop * Apache Spark * Amazon Elastic MapReduce * Microsoft's Azure HDInsight * Google Cloud Dataproc In cloud environments, big data can be stored in: * Hadoop Distributed File System (HDFS). * Lower-cost cloud object storage, such as Amazon Simple Storage Service (S3). * NoSQL databases. * Kafka, an application-to-application messaging and data streaming platform; * the H base database; and * SQL-on-Hadoop query engines like Drill, Hive, Impala and Presto.

20. 20. Conclusion * Big Data is defined as data that is huge in size. Big data is a term used to describe a collection of data that is huge in size and yet growing exponentially with time. * Examples of Big Data generation includes stock exchanges, social media sites, jet engines, etc. * Big Data could be 1) Structured, 2) Unstructured, 3) Semi-structured * Volume, Variety, Velocity, and Variability are few Characteristics of Big data * Improved customer service, better operational efficiency, Better Decision Making are few advantages of Big data. * These are truly revolutionary times if both business and technology professionals continue to work together and deliver on the promise. * Genuine leap forward and a clear opportunity to realize enormous gains in terms of efficiency, productivity, revenue, and profitability.

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Published on Big Data(Mckinsey Report) 1. Report on: Big data The next frontier for innovation, competition, and productivity. 2. What do we mean by "big data"? * Big Data is also data but with a huge size. Big Data is a term used to describe a collection of data that is huge in size and yet growing exponentially with time.

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big data is a must

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Sudah punya

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Big Data In 5 Minutes | What Is Big Data?| Big Data Analytics | Big Data Tutorial | Simplilearn