Foreword
With the end of the era of flow of dividends, the Internet ushered in a more refined user with the order of the times. Today, from the data, in-depth understanding of user behavior, continuous optimization of products, marketing and operations, the key to winning business. In this context, data analysis platform an essential tool to help companies achieve "data-driven" and refinement of operations.
Well, today's business needs in the end what kind of data analysis platform? How to make data analysis fast landing platform in the enterprise, truly "speak with the data" so that data to create real value for the enterprise? With these questions, the selection Bao live interview with founder and CEO Sang Wen-feng of Chinese big data analytics industry pioneer Shence data.
The following is part of the essence of what we sort of dialogue based on this interview, hoping to inspire all of us.
What is "data analysis platform"?
Data analysis Why has increasingly become a focus of attention?
Data analysis contains links which
can bring what kind of value to the business?
With the rise of mobile Internet traffic and dividend away, the development of the Internet has bid farewell to the era of the past flow into the more challenging the user with the order of the times. New Age wisdom of decision-making, operations and product capacity of enterprises and so put forward higher requirements, and behind this, you need to have the appropriate data and analytical tools do support.
Today, more and more enterprises begin to practice the "data-driven", by means of data analysis, to achieve fine intelligence operations and products to enhance the competitiveness of enterprises, and the role of data analysis platform is to make data analysis becomes more scientific and more efficient.
In recent years, data analysis gets more and more attention, becoming an increasingly hot topic, I think there are three main reasons. First, with the development of mobile Internet and IoT technologies and data resources has become increasingly diverse, we can get past the reach of a lot of data today; second, data processing capabilities continue to increase, there has been Hadoop, Spark and other new technologies the new framework; third, people's growing awareness of data, with data analysis, and strengthen competitive advantage has become a consensus.
Data analysis typically contains four areas: data collection, modeling, analysis, index system.
Data analysis for the value of the enterprise, I summed up in three points: first, through the whole end of the data collection, building the foundation of enterprise data; the second is data-driven business decisions, that is, BI; Third, intelligent data-driven product, but also is the AI.
What is the best practice data-driven?
How to make faster data analysis platform in the enterprise
better landing?
Data analysis and selection of best practices platform for data-driven
The biggest challenge for data-driven enterprise data base is thin, poor data awareness. So, I think, to practice data-driven, first, to lay the foundation put data, the second is to establish a full role, the whole channel, data awareness of the whole process, the third is to make good use of data analysis tools, using tools to improve the efficiency of data collection and analysis.
Selection comes to data analysis tools, I think, in addition to the matching function, safety, flexibility and other indicators, enterprises should study focused on service providers the ability to deliver implementation and follow-up service and support levels.