Make smarter business decisions with large data

Make smarter business decisions with large data

It turns out that, like technology solutions, it takes skill to achieve success with large data.

Newvantage with executives from more than 50 large companies (Chief Data Officer, CIO, CTO, chief analyst, chief information architect), business executives and senior programmers last summer. Most of these large companies have more than 30000 employees. In the Newvantage Partners survey, half of the respondents were executives from financial services companies, while the other half were executives from insurance companies, government agencies and other industries.

"Most companies spend 1 billion dollars a year on technology," said Paul Barth, founder and managing partner of Newvantage Partners. They usually don't respond quickly, but once they start responding, they will invest more money and resources into these innovations. ”

Make smarter decisions with big data

These large companies see the value of large data and begin to invest their resources in big data. Barth said 85% of respondents said they were making big data innovations.

"75% of respondents spend more than 1 million dollars a year on big data," he said. 25% of respondents spend more than 10 million dollars a year on big data. They adhere to the commitment to apply this technology to a project or a series of projects. Because they know very well that if there is no big data, the project in their hands will not go on. ”

The real value of large data is the increased response speed

Respondents gave many reasons for investing in big data, such as reducing risk, creating high-quality products and services. However, the top two main reasons are: make decisions faster and improve the customer experience, depending on the situation. Of course, this is the first reason they invest in traditional business intelligence analysis. In conducting an in-depth investigation, Barth said, Newvantage found that the underlying reason for the companies ' investment in large data was the desire to improve decision-making or response speed.

"If your response rate is 30 minutes in a case and 30 seconds in another case, it will actually change your business process," Barth said. They will make you a highly efficient business analyst. ”

With big data technology, he says, companies can respond to problems within seconds, rather than spending days or months. This promotion, in turn, enables companies to respond to problems that are difficult to analyze, develop testing, and process learning but quickly adapt to the marketplace and automate complex workflows.

However, a rigorous process is needed to make the most of the benefits of shortening the response time. The relationship between large data and traditional analytical solutions should be clearly defined and dependent, as they are the basis for the process.

Large data, analytical methods and organizational adjustment

The report notes that "the distinction between traditional and large data, and the organizational responsibility they undertake separately within the enterprise, has been discussed many times before." However, surveys show that traditional analytical methods and large data are becoming increasingly complex. They have to work together to make the expected effect of large data. In the future, closer integration between it and business to break the boundaries of the organization will be a key step for the company to develop a large data strategy for success. ”

"Data management and analysis is usually the responsibility of different parts of the company," the report said. "The IT department usually controls the data, and the analysis is the responsibility of a particular team or department in the company." This completely violates the principle of large data. Surveys show that these companies have recognized the need for close integration. 65% of respondents said large data is a major part of data management. 68% of respondents said big data was part of the Advanced analysis tool. ”

Newvantage concluded that breaking the boundaries between it and the business sector, and consolidating traditional analytics with large data, was a major leap forward, an early and critical step towards achieving the institutional innovation of large data for business development.

"Integrating real-time, complete analytics into the business and operations sector enables companies to respond quickly to key business issues and challenges, creating a competitive advantage for the company and helping it improve its performance," the report said. ”

"According to the data and the quality of the data, we divide them into three different grades of gold, silver and copper," Barth said. The data stored in the Data Warehouse is the gold data. When you query the gold data, you know that the data has been processed. But what if the data is in the original form and is available to me in a week or one months, and what if you put all the data in one place and basically don't comb them? This data is useful until it is fully refined. ”

Unlike traditional relational databases, large data platforms allow analysts to selectively organize, clean, and consolidate data, ignoring records and fields that are not currently the focus of analysis. This allows you to get rid of the data warehouse and avoid putting a lot of effort into data engineering. Newvantage points out that by delaying the entire data project, the large data platform improves the response speed in the discovery-oriented analysis without the need for engineering analysis of data that cannot provide value.

Barth says the big data platform has become a very important data biosphere. Although the biosphere is built on what is known, the biosphere is designed to continually look for new insights from customers, markets, products and risks. In other words, it is through the "already", healthy continuous improvement model to find "new" things.

(Responsible editor: Lu Guang)