Facing the vast ocean of data, how companies can reach the other side of victory and enter the digital age smoothly has become a problem that all companies must face.
This is not alarmist.
In 2019, SAP and Intel commissioned Forrester Consulting to conduct a customized study on "how companies meet data management needs to support their business goals" and reached clear conclusions.
That is, "In order to achieve business transformation, companies must use intelligent applications and data analysis solutions to collect, process, and analyze a large number of different data in real time. However, obtaining value from the massive and diverse data that they master is still a problem faced by many companies today. In particular, the continuous innovation of technology platforms and deployment models (such as the cloud) has increased the difficulty for enterprises to achieve a truly data-driven model in the past decade."
In other words, data has become a core element that affects the success of an enterprise's business, but for various reasons, such as overly complex tools, rapid technological iteration, and rapid data growth, it is difficult for enterprises to obtain value from data.
First of all, I will emphasize the background of the interview. In order to complete the study, Forrester interviewed 353 decision makers of data management strategies in key countries around the world. Among them, 42% were from the United Kingdom, France and Germany, 29% were from the United States, 28% were from China and Japan; The number of employees ranges from more than 5,000, and is evenly distributed; the respondent’s department has both IT, and is responsible for enterprise architecture and business lines; the level of the respondent includes senior IT/data director, IT vice president, IT director, IT/ Data manager.
There is no doubt that this is a fair and comprehensive investigation and research, so the conclusions drawn can be used for reference.
Let's take a look at the specific content of this research, hoping to inspire you.
consensus:
Business success is closely related to data insights
In the survey, respondents firmly believed that data-driven intelligence is inseparable from the success of today's business decisions. In other words, data insight has become a key force for enterprises to win the future.
In the process of data insight, "real-time analysis and insight", "performance optimization", "data management automation" and "intelligent business applications based on artificial intelligence and machine learning" are considered to be the most important capabilities. One-third of respondents believe that these four points are the primary factors affecting business success.
In addition, the simplification and automation of data management are also capabilities that enterprises pay more attention to.
The elements of "real-time analysis and insight" and "performance optimization" are well understood and are related to efficiency. Why do users pay so much attention to simplicity and automation? It's very simple, Gartner has already studied it. Gartner predicts that in the next three years, the popularization of data analysis knowledge and technology will accelerate, enabling employees of major companies and organizations to use advanced data analysis functions to obtain valuable and usable insights from data. Simplification and automation of data insights that ordinary employees can achieve are essential elements.
challenge:
The road to data-driven business is full of thorns
Continuously generated new data, tools that are not humane enough, and a large number of data islands to be integrated...result in the inability to fully release the value of data. Data-driven business is difficult.
In the survey, 61% of respondents encountered system limitations when collecting and analyzing large amounts of data; 55% of respondents could not access data through self-service and require a lot of IT participation; data/application complexity caused data 48% of islands are difficult to integrate.
These are just the tip of the iceberg of challenges facing data insights. In addition, complex tool ecosystems and endless new technologies have profoundly affected the direction of enterprise data insights.
Take the tool ecosystem as an example. For most companies, data management is extremely complex, because a large number of different data storage, access and integration solutions are used in various environments and at different times, plus complex data lifecycle management tools and processes, data Governance schemes, as well as the solutions needed to expand data management according to business needs, form a very challenging data governance environment.
This brings a series of challenges, such as rising costs, increased risks, and slower value realization. In the survey, more than half of the companies encountered these problems.
Look at the new technology. The most successful new technology in recent years is the cloud, which has gone from no one to no one in ten years. With the continuous popularization of cloud as the underlying technology, data management technology will inevitably follow. In this survey, more than 90% of respondents are expanding, implementing or planning to implement a cloud-based database management system (DBMS). And this means that the already highly complex data environment will become more difficult.
future:
A more powerful data management platform is the cornerstone
Faced with various challenges, a more powerful data management platform has become a must for enterprises. In the survey, respondents also gave their most urgent needs. The top three are data virtualization, security and data privacy, and data consumption flexibility.
The conclusion may deviate from everyone's imagination, and safety is not the first. In fact, there is no contradiction, after all, there is no efficiency, and there is no value in talking about safety. Data virtualization is about efficiency and is closely related to real-time analysis. In Forrester's definition, data virtualization refers to the integration of any data from structured, unstructured and semi-structured data sources in real-time or near real-time.
In order to improve efficiency, another relatively clear data governance path has gradually become clear, and that is the application of in-memory databases. In the survey, nearly 70% of companies have begun to implement in-memory databases to alleviate certain problems. In addition, 28% of companies are planning to implement or are interested in the technology.
In the survey, respondents believe that in-memory databases can bring many advantages both at the technical level and at the business level. For example, at the technical level, because multiple data types and workloads can be managed without using multiple tools, companies can not only improve data integrity by supporting transaction analysis and processing, but also accelerate development and improve process efficiency. At the same time, technical advantages can further contribute to business advantages, especially improving business process efficiency, increasing employee productivity, and real-time data access.
In the application of in-memory databases, Intel Optane persistent memory (hereinafter referred to as "Aotane") is an important technological innovation. By virtue of providing more persistent memory capacity (no data loss in the event of power failure), it has DRAM's performance and lower cost advantages have been praised by many interviewees.
In the survey, 61% of respondents believe that Optane can improve the ability of real-time analysis of transaction data in the same system; 61% believe that Optane can optimize HA/DR operations by speeding up database startup and reduce system downtime; 58 % Believe that Optane can enhance the scalability of high-performance, large-scale data analysis systems.
In fact, there are already many applications of Optane to greatly improve the performance of in-memory databases, including SAP HANA, Oracle, and a variety of open source databases that have demonstrated better performance after being equipped with Optane.
For example, recently, HPE Superdome Flex set a world record of overall performance and 16-processor performance with 41.6 billion initial records in the SAP HANA standard application benchmark version of the SAP Business Warehouse version. The Superdome Flex used in the test is equipped with 16 second-generation Intel Xeon Platinum 8280L processors, 12 TB DRAM and 12 TB HPE persistent memory. Prior to this, HPE Superdome Flex created a world record of 20.8 billion initial records in October 2019 with the same Intel Xeon processor and 12TB DRAM configuration. 12TB persistent memory, double the performance, very impressive.
To summarize the full text, with the continuous improvement of data processing capabilities and large-scale data storage and retrieval capabilities, it has become possible for companies to achieve true business innovation and competitive differentiation. However, the problem is also serious. If you want to keep up with the pace of change and make a choice among the dazzling technical solutions, the biggest uncertainty is.
The core of Forrester's recommendation is one sentence: a suitable data management platform to handle massive data in different formats for multiple use cases in a multi-cloud and hybrid environment, while simplifying access and reducing IT complexity. My suggestion is to find strong and capable suppliers to talk more about, after all, they are more professional in terms of technology.
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