Treatment for this disease! Large boom of those led astray-big data Garner,Narrative Science-IT information

To understand anything, you need to keep track of it. This is because you know what you′re doing--whether we′re talking about sales, logistics, customer service, or anything else--understood, is the first step can do better. Unfortunately, simple tracking data will not let you go further. To make it worthwhile, you must get some meaningful inspiration.

Collecting data is very easy, but to remove noise and get rid of the most irrelevant thing is full of challenges. That′s why, does not make our lives easier or increase our productivity, and in many cases, data is really just creates more work.

You know what I meant, and this time, we spent a lot of time and effort than before to collect, analyze, interpret and explain. In fact, compared with the actual results expressed, employees are putting more effort into preparing analyses on the data. And to make matters worse, in some cases, the organizers under the throne of wealth are sitting on large amounts of data, the data can be transformed into new revenue opportunities, but they don′t use it to do, because they don′t have the time or the resources to use it.

Big data is overrated?

In an ideal world, the data will be used for us. We like to be able to quickly gain insight, promote development of new products, provides our customers with relevant information, and ultimately make better business decisions. Unfortunately, we don′t live in a world of understanding, data do not always break.

You don′t believe me? When it comes to data when I′m not the only one who suggested, we seem to be blindly optimistic would be a mistake. Refer to the following:

According to Garner′s recent report, 60% of large data projects will be through pilot and experimental, and was eventually abandoned. Gartner research shows that the interpretation of values from data is for those who intend to invest in its people′s number one challenge.

The CEO of Pneuron, and (Pneuron is a system developed for the Organization and business process platform), shared in a single value before they are created, 70% of enterprise projects is used to identify, aggregate, moving, storage and optimize data.

This and other studies show that data is not a bad thing. In contrast, if you meaningful insights to be gained, there is no doubt that you will advance your career. The trick is, you have to be smart. Collecting high quality data is very important, the company won big data games, learn how to use it effectively. Inherent risk of data is that people tend to watch the models with no real existence.

So how can companies make better use of their data? How they use the data to improve their business, and not in too much data and too little time into it?

The answer is that before you start tracking and managing any data, you need to understand what you want trying to solve business challenges.

Here is an example.

I was recently working with a credit card company. Because he has gained a large amount of data--collected and analyzed extensive information on business activities, including when, where and how their customers buy--it′s also an effective data company.

Through monthly merchant monthly the company′s challenge is to convey all the data in a meaningful way, seen from the past, these reports are quite basic, containing only a few simple survey, for example, graphically convey the customer′s monthly average. Because the report was based on all available data, rather than a set of insightful point of view, they are very general, and does not provide a meaningful introduction to. Not surprisingly, readers of utilization is very low.

Better, not more

The company needs by answering who some important issues, find the data most important to their readers. For example:

What kind of customers spent the most money in my store?

They are usually what time shopping?

At this time of the day, I can do some kind of extra promotions to increase store and customer relationships?

In this way, they can focus on the most important data. Not just to businesses reported more insightful information, and analysis easier to manage.

Correct application of data is not easy. Many companies don′t realize that the data itself is not the answer, so they gather as much data as possible. Reality is that you need to select use data. Select information from the business challenge and home, will give you the most valuable insights. Was lucky, although excessive amounts of data has been a problem, it is also a catalyst for new technology to overcome those difficulties. Similar to prediction and analysis of technologies, advanced natural language generation and intelligent data discovery solutions, can help you achieve real value from your data. These data not only bigger, but better.

这病得治！大数据繁荣期的那些歧途 - 大数据,Garner,Narrative Science - IT资讯

要了解任何事情，你需要跟踪它。这是因为你知道你在做什么——不管我们在讨论销售，物流，客户服务或其他什么——了解，是能做的更好的第一步。不幸的是，简单的跟踪数据不会让你走的更远。要让它变的有价值，你必须从中得到有意义的启示。

收集数据是很容易的，但是能够切除噪声和把最无关紧要的事情处理掉却充满了挑战。这就是为什么，数据并没有让我们的生活更容易或者提高我们的生产力，很多情况下，数据实际上只是创造了更多的工作。

你知道我的意思，这段时间，我们比之前花了很多的时间和精力收集，分析，诠释和解释。事实上，与实际表达结果相比，员工把更多的精力投入到准备分析数据上。更糟糕的是，在某些情况下，组织者们正坐在大量数据的财富宝座下，这些数据本可以转变成新的收入机会，但是他们没有用它来做什么，因为他们根本就没有时间和资源来使用它。

大数据被高估了？

在一个理想的世界里，大数据将会为我们所用。我们喜欢能够很快获得洞察力，促进新产品开发，为我们的客户提供相关的信息，并最终做出更明智的业务决策。不幸的是，我们并不是生活在一个理解的世界中，大数据并不是总能被破解的。

你不相信我吗？当谈到大数据的时候，我并不是唯一一个这么建议的，我们看似盲目的乐观可能是错误的。参考如下：

根据Garner最近的报告，60%的大数据项目将会无法通过试点和实验，并且最终被抛弃。Gartner另外的研究表明，从大数据中诠释价值是为了那些打算投资于它的人的第一号挑战。

Pneuron的CEO，(Pneuron是一个为组织提高系统开发和业务处理的平台)，分享了在一个单一的价值被创造出来之前，70%的企业项目是用于识别，聚合，移动，存储和优化数据。

这和其他研究表明，大数据并不是不好的事情。相反，如果你可以从中获得有意义的见解，毫无疑问你会改进你的事业。诀窍是，你必须是聪明的。收集高质量的数据是非常重要的，公司赢得大数据的比赛，了解如何有效的利用它。大数据内在的危险在于，人们往往倾向于观察那些实际并不存在的模式。

那么企业如何才能更好地利用他们的数据呢？他们如何利用数据来改善他们的业务，而不是陷入太多数据和太少时间的陷进里呢？

答案是，在你开始跟踪和管理任何数据之前，你需要了解你想要试图解决的业务挑战。

这里有一个例子。

我最近与一家信用卡公司合作。因为他已经获得了大量的数据——它收集和分析了关于商人活动的大量信息，包括何时，何地以及他们的客户如何购买——它也是一个有效的数据公司。

该公司的挑战是通过每月的商人月报以一种有意义的方式传达所有的数据，从往期看，这些报告相当基本，只包含一些简单的调查结果，例如，通过图表形式传达客户的每月平均花费。因为报告是基于所有可用的数据，而不是一组见解深刻的观点，它们非常一般，并没有提供有意义的简介。不出所料，读者的报告利用率是相当低的。

更好，而不是更大

这个公司需要通过回答这些商人一些重要的问题，找到对他们的读者来说最重要的数据。例如：

哪一类客户在我的商店里花了最多的钱？

他们通常是什么时间购物？

在每天的这个时候，我还可以做一些什么样的额外促销去增加商店和客户之间的关系？

通过这种方法，他们可以关注到最重要的数据上。不仅仅是给商家的报告有更多的洞察信息，也让分析易于管理。

正确的应用大数据并不容易。很多公司没有意识到数据本身并不是答案，因此，他们认为收集越多的数据越好。现实是你需要有选择地使用数据。从商业挑战和家里挑选信息，会给你最有价值的见解。幸运的是，虽然过多的数据已经成为一个问题，它也是克服那些困难的新技术的催化剂。类似于预测分析的技术，先进的自然语言生成和智能数据发现解决方案，可以帮助你从你的数据中实现真正的价值。这些数据并不仅仅是更大，而是更好。