Image via CrunchBaseBig Data: Big News Facebook And Big Data
After reading this you appreciate your Facebook stream just a little more.
O'Reilly Radar: What is big data?
Big data is data that exceeds the processing capacity of conventional database systems. The data is too big, moves too fast, or doesn't fit the strictures of your database architectures. ..... cost-effective approaches have emerged to tame the volume, velocity and variability of massive data. Within this data lie valuable patterns and information ...... Today's commodity hardware, cloud architectures and open source software bring big data processing into the reach of the less well-resourced. ...... analytical use, and enabling new products ...... Being able to process every item of data in reasonable time removes the troublesome need for sampling ...... by combining a large number of signals from a user's actions and those of their friends, Facebook has been able to craft a highly personalized user experience and create a new kind of advertising business. It's no coincidence that the lion's share of ideas and tools underpinning big data have emerged from Google, Yahoo, Amazon and Facebook. ....... The emergence of big data into the enterprise brings with it a necessary counterpart: agility. Successfully exploiting the value in big data requires experimentation and exploration. ........ Input data to big data systems could be chatter from social networks, web server logs, traffic flow sensors, satellite imagery, broadcast audio streams, banking transactions, MP3s of rock music, the content of web pages, scans of government documents, GPS trails, telemetry from automobiles, financial market data, the list goes on. ....... the three Vs of volume, velocity and variety are commonly used to characterize different aspects of big data. ........ Having more data beats out having better models ...... If you could run that forecast taking into account 300 factors rather than 6, could you predict demand better? ......... Many companies already have large amounts of archived data, perhaps in the form of logs, but not the capacity to process it. ...... data warehouses or databases such as Greenplum — and Apache Hadoop-based solutions ...... Apache Hadoop.. places no conditions on the structure of the data it can process. ...... First developed and released as open source by Yahoo, it implements the MapReduce approach pioneered by Google in compiling its search indexes. Hadoop's MapReduce involves distributing a dataset among multiple servers and operating on the data: the "map" stage. The partial results are then recombined: the "reduce" stage. ......... Hadoop is not itself a database or data warehouse solution, but can act as an analytical adjunct to one. ....... A MySQL database stores the core data. This is then reflected into Hadoop, where computations occur, such as creating recommendations for you based on your friends' interests. Facebook then transfers the results back into MySQL, for use in pages served to users. ............ the increasing rate at which data flows into an organization — has followed a similar pattern to that of volume. Problems previously restricted to segments of industry are now presenting themselves in a much broader setting. Specialized companies such as financial traders have long turned systems that cope with fast moving data to their advantage. Now it's our turn. ......... Online retailers are able to compile large histories of customers' every click and interaction: not just the final sales. Those who are able to quickly utilize that information, by recommending additional purchases, for instance, gain competitive advantage. The smartphone era increases again the rate of data inflow, as consumers carry with them a streaming source of geolocated imagery and audio data. ......... The importance lies in the speed of the feedback loop, taking data from input through to decision. ........ you wouldn't cross the road if all you had was a five-minute old snapshot of traffic location. ......... "streaming data," or "complex event processing." ...... when the input data are too fast to store in their entirety: in order to keep storage requirements practical some level of analysis must occur as the data streams in. ........ At the extreme end of the scale, the Large Hadron Collider at CERN generates so much data that scientists must discard the overwhelming majority of it — hoping hard they've not thrown away anything useful. The second reason to consider streaming is where the application mandates immediate response to the data. Thanks to the rise of mobile applications and online gaming this is an increasingly common situation. ........ The velocity of a system's outputs can matter too. The tighter the feedback loop, the greater the competitive advantage. ....... Rarely does data present itself in a form perfectly ordered and ready for processing. A common theme in big data systems is that the source data is diverse, and doesn't fall into neat relational structures. It could be text from social networks, image data, a raw feed directly from a sensor source. None of these things come ready for integration into an application. .......... the reality of data is messy. Different browsers send different data, users withhold information, they may be using differing software versions or vendors to communicate with you. And you can bet that if part of the process involves a human, there will be error and inconsistency. ....... Is this city London, England, or London, Texas? By the time your business logic gets to it, you don't want to be guessing. ...... a principle of big data: when you can, keep everything. There may well be useful signals in the bits you throw away. ....... documents encoded as XML are most versatile when stored in a dedicated XML store such as MarkLogic. Social network relations are graphs by nature, and graph databases such as Neo4J make operations on them simpler and more efficient. ....... a disadvantage of the relational database is the static nature of its schemas. In an agile, exploratory environment, the results of computations will evolve with the detection and extraction of more signals. Semi-structured NoSQL databases meet this need for flexibility: they provide enough structure to organize data, but do not require the exact schema of the data before storing it. ........ three forms: software-only, as an appliance or cloud-based. ...... IT is undergoing an inversion of priorities: it's the program that needs to move, not the data. .... Financial trading systems crowd into data centers to get the fastest connection to source data, because that millisecond difference in processing time equates to competitive advantage. ...... 80% of the effort involved in dealing with data is cleaning it up in the first place ...... data science, a discipline that combines math, programming and scientific instinct. ...... The art and practice of visualizing data is becoming ever more important in bridging the human-computer gap to mediate analytical insight in a meaningful way. ...... advice to businesses starting out with big data: first, decide what problem you want to solve.
