Everything in the big data

What's the big data? Why use large data? What are the popular tools for big data? This article will answer for you. See the original: Get the Complete Story with large data analytics Author: Kayden Kelly Now, Big data is an abused buzzword, but its real value even a small business can achieve. By consolidating data from different sources, such as web analytics, social data, users, and local data, large data can help you understand the overall situation. Large data analysis is becoming more and more easy, costs are getting lower, and it is easier to accelerate business understanding than before. Large data is commonly associated with enterprise business Intelligence (BI) and data warehousing: high cost, high difficulty, and high risk. Previous initiatives in business intelligence and data warehousing failed because they took months, or even years, for shareholders to get quantifiable benefits. But that's not the case, and you can actually get the real intention on that day, at least for a few weeks. Why use large data? The data is growing at an explosive rate. One notable example comes from our customers, most of whom use Google Analytics. When they analyze a long period of data or use advanced segmentation, the data that Google analyzes starts sampling, which makes the real value of the data hidden. Now our tool CLICKSTREAMR can collect a huge amount of data at the click Level, so you can track every click behavior in the user's access path (or access stream). In addition, if you add some other data sources, he really becomes big data. More complete parsing of large data is not just a lot of data. His real meaning is to complete a more complete report based on the relevant data background. For example, if you add your CRM data to your site's data analysis, you might find a High-value user base you already know. They are women, living on the West Coast, ages 30 to 45, and spend a lot of time at Pinterest and Facebook. Now that you've been armed with this knowledge, that's how to effectively set and get more High-value users. Companies like tableau and Google have brought more powerful data analysis tools (such as large data analysis) to users. Tableau provides a solution for visual analytics software that costs 2000 dollars a year. Google provides bigquery tools that allow you to analyze your data in minutes and meet any budget requirements. What's the big data? Since large data is often a hybrid, semi-structured, and unstructured data, large data becomes difficult to correlate, process, and manage, especially with traditional relational databases. When it comes to big data, Gartner (Gartner Group), founded in 1979, is the first information technology research and analysisCompany analyst divides it into 3 V: Magnitude (Volume): A large number of data rates (velocity): high-speed data-output diversity (produced): multiple types and sources of data. As we said, most businesses produce large amounts of data each day in different fields. Here gives a set of sample data source and type, they are the enterprise in the large data analysis of potential collection and aggregation of data in the way: Web Analytics Mobile Analysis equipment/sensor data user data (CRM) unified Enterprise Data (ERP) Social data accounting system point-of-sale system sales system Consumer data (e.g., profit-making data, Dunkleosteus data or census data) company internal spreadsheet company Internal Database location data (space position, GPS location) weather data but for unlimited data sources, don't do too many things. Focus on the relevant data and start with small data. Usually starting with 2-3 data sources is a good idea, such as Web site data, consumer data, and CRM, which will give you some valuable insights. After you first enter a large data analysis, you can start adding data sources to facilitate your analysis and publish more analysis results. For more information on the details of large data, check out Wikipedia's Big data entry. Large data benefits large data provides a forward-looking approach to identifying and leveraging high-value opportunities. If you want, then large data can provide the following benefits: Get a more complete picture based on the data background use data driven to make better business decisions reduce the best solutions in the business risk market develop better customized products or services better predict customer needs and ideas quickly adapt to the market More proactively establishing accurate life cycle (LTV), maps, and user type reading in real-time data trends and forecasts (for Web site click Stream data) to visualize more complex navigation through subdivision, and improve your conversion funnel (for Web site click Stream data) does not apply to everyone please remember that large data analysis is not for everyone. If you're not installing and setting goals for analysis, not being prepared for attribution models, marketing, and advanced segmentation, you're not ready for big data. If you use Google Analytics to the limit, especially because of his sampling data. Then you are ready to touch the fur of the big data. Entry-Level large data solutions currently have a large number of enterprise-wide data solutions, such as Oracle, SAP, IBM, EMC, and HP. But. This article is for readers of small and medium-sized businesses looking for entry-level, large data-solutions. Here we'll discuss the output of data analysis and share two relatively inexpensive solutions to help you get started with large data analysis. The output of analysis results for most enterprises, data analysis is mainly focused on core data. In the future, however, dataThe analysis will not take the sampled data and will be analyzed using more sophisticated tools such as tableau, combined with data from other sources. Google Analytics is a great tool, but the results you can get are now at an extreme. The first step in summarizing data is often the process of analyzing your output data. If you are a Google Analytics Advanced version of the user, it will be easy to push forward. Because the Google Analytics Advanced Edition integrates the BigQuery feature to help companies drive large data analysis. (To learn more about data analysis and BigQuery integration, check the video) If you are a Google Analytics standard version of the user, do not worry. We've developed a tool that can export an bigquery of Google Analytics data and push it to a data warehouse or data tool that can make data analysis bigger. (Note: You may also notice other tools that can export Google Analytics for not-sampled data, but the difference is that this is our main job.) As a consulting firm with Google Analytics, we often have to help customers export data that is not sampled for reporting purposes. But when we found some problems with other tools, we had to create a more reliable solution ourselves. Once you have exported your data, you can be prepared to import it into a large data analysis tool for storage, processing, and visualization. This brings us to the best entry-level large data solution. Google's big Data solution Google BigQuery is a Web service that allows you to perform billions of of rows of interactive analytics on a large dataset. The important thing is that it's easy to use and allows savvy users to develop larger functionality based on requirements. BigQuery uses your affordable pricing principle, and when you start to store and process your large data queries, you spend only hundreds of dollars a month. In fact, 100GB of data processing is free every month before. As you grow in demand, you can expand your data needs and pay for this part of the demand. The best news is that BigQuery makes large data storage and processing available to everyone. Tableau Large Data Solutions Tableau provides 4 powerful features (perhaps more) to facilitate large data analysis and predictive analysis. Salesforce connectors allow you to easily connect CRM and sales data (faster, easier to connect CRM and sales data, so if you use Salesforce, there is no reason not to add large data) Google Analytics links can help you create custom dashboards and reports more easily (but this feature still needs to be upgraded to be better) Google BigQuery connectors can quickly analyze a lot of data in Google's free web services. Add predictive functionality for any click analysis (really fast prediction) data analyst is the key enterprise want to take advantage of large data, it needs a data analyst. He had to know the use of different data,and to grant the tool the right to connect to the data. When a data analyst uses BigQuery or tableau to extract and merge data, they can discover hidden patterns in large data sets. That's the key to big data analysis. It can be a decision maker to make better decisions and to enhance the recognition of finer granularity of data segments. With this new skill, you can find different user interactions with the site. You can use this in Google Analytics to create new advanced segmentation rules and to make a higher value analysis of your marketing or website activities. Discover the value of an unknown situation in which you have a lot of different data hidden in an unknown situation that you want to be found and informed. Start to combine web analytics, CRM, social data, location data, and other data sources. This gives your data a background and allows you to see a more complete picture through the data. This will definitely make you a competitor. To illustrate this point, for example, by summarizing social data, location data, customer data, and sales data through large data analysis, you can find trends in the social media in San Francisco. This allows you to increase the inventory of specific areas by leveraging the increase in user needs. Don't forget the golden rule of Big Data analysis: Focus on the right business issues at the right time. If you like this article, please share it with a little praise. Don't hesitate to ask questions and keep communication with me.