For many organizations, how to successfully build a cloud
data warehouse for the first time is a difficult problem, so we need to know some knowledge and skills.
How should organizations enter this unknown field? Building and using cloud data warehouse for the first time may sound daunting, but for organizations that want to better classify their data, cloud data warehouse is a feasible choice, and cloud platforms usually allow flexibility and scalability.
A recent study by data virtualization provider denodo found that 56% of organizations deployed
data warehouse technology in the cloud platform, and often found that they could obtain many benefits, including effective workload management and vendor locking.
However, organizations trying to use this technology for the first time may want to know where to start, and if they fail, it will be costly in terms of time and cost. So what should organizations do to significantly reduce risk and ensure return?
1. Improve labor skills
One issue that needs to be addressed is to ensure that the organization's staff skills are ready for transition.
One of the main aspects of cloud data warehouse technology is that it provides a large amount of data and is very useful in monitoring customer behavior. However, if the employees of the organization do not have enough skills to know how to use it correctly, they will not be able to realize its potential.
Thomas Larock, chief technology officer of solarwinds, said, "building data warehouses around the world with low latency and huge computing power is no longer beyond the reach of standard businesses. What used to cost millions of dollars to do now takes only a few hundred dollars and some PowerShell scripts.
Organizations can easily leverage cloud computing providers to allocate hardware resources for their data analysis needs. However, there is no doubt that handling big data requires serious skill upgrading. But these new skills will broaden the horizons of IT professionals in organizations. A good understanding of data processing, coupled with traditional network engineering, will ultimately promote the career development of IT professionals, so it should be seen as a necessary investment. "
2. Establish adequate data governance
Larock continues to stress the importance of ensuring that organizational data is managed in a way that does not generate useless duplicate or isolated data.
"The most common pitfall in implementing a data warehouse is managing, collecting, and aggregating multiple copies of the same data," he said. Enterprises usually have a lot of data warehouses, if they form part of the data warehouse, there will be redundancy. If you want to start building a cloud data warehouse, you must consider establishing an appropriate data governance strategy. With this strategy, you can identify islands before you implement the data warehouse. "
3. Start small
When an organization tries to build a cloud data warehouse for the first time, it is best to minimize the risk of errors by reducing expectations.
Craig Stewart, chief technology officer of snaplogic, said: "it's going to be a small process to start with, gain some experience and value in a small project, and then learn from it. Gain experience from the first project, and then gradually gain more value.
The great thing about cloud computing is that organizations can increase the resilience they get from things like redshift and azure synapse, which really enables organizations to do that. Starting from small things means that if the project that the organization tries fails, it can learn from the experience and lessons, and then continue to the next step, without having to pay a huge cost, whether it is the source of funds or the cost of human resources.
Use a non code type tool in self-service mode. This combination means that the organization can seek for rapid value acquisition, and what learning has done does not bring value to the organization, and then it can also develop rapidly without encountering very expensive failure, which itself is a learning process of value acquisition. "
4. Planning a new architecture is the key
In addition to starting small, it is critical that organizations be patient by carefully planning their cloud data warehouse architecture.
Rob Mellor, vice president of wherescape and general manager for Europe, the Middle East and Africa, said: "organizations need to pay attention to some of the misinformation they will hear in the research process. Organizations can not only put all data into the cloud platform, but also start to analyze it without any design or architecture. The analysis environment is planned and architected so that it can be understood and used by all users.
Organizations also don't need to migrate all their data warehouses to the cloud without having to redesign them. There are many troubles in the process of data warehouse cleaning.
But it's a good time for organizations to clean up inefficient processes and waste unused assets such as old reports, visualizations, and analytics that are no longer in use. This is also a great opportunity to automate many processes to improve their efficiency. "
6. Using existing models
The decision to migrate the data warehouse to the cloud for the first time may not require complete new work and may require learning from existing architectures that need to be improved.
Among other benefits, this can help organizations meet the above requirements for adequate data governance.
"Migration should be seen as an opportunity to rationalize and modify existing local data warehouses," said Helena schwenk, marketing intelligence manager at exasol. Organizations need to identify which data assets and sources can be modified, expanded or added, and adopt a gradual migration strategy to achieve a cohesive cloud data warehouse platform, including appropriate governance and oversight. "
7. Ensure possible evolution
Schwenk says organizations need to understand the importance of using data other than those that are often used internally. Big data (especially public cloud) of cloud computing can benefit from the integration of external influences.
"Organizations need to study how the public cloud supports new data workloads or business use cases," she said. For example, consider using the scale and flexibility of cloud data warehouse to support more data for analysis, so as to support advanced analysis and data science in cloud data warehouse. Those updated cloud native data sources (such as social media data and data from sensors) may benefit greatly in providing a deeper and deeper understanding of the business. "
8. Consider serverless Technology
Justin goodenough, international vice president, unravel data, recommends considering serverless technology.
"Serverless relational databases are a common choice for business intelligence applications and publishing data for use by other systems," he said. They provide scale, performance, and, most importantly, SQL based access to prepared data.
These are useful for moderately sized and relatively simple data structures.
For higher performance and complex relational data models, large-scale parallel processing (MPP) databases store large amounts of data in memory, and can develop rapidly, but often at a high cost. "
9. Research and seek professional knowledge
Finally, two tips to consider when you first start using cloud data warehouse technology may apply to any new business activity, or even life risks.
GM Lyons, general manager of cloud computing and hosting at Zen Internet, said, "it's important to understand exactly what an organization needs to look for, because different platforms have different advantages in data types, analysis and processing. For example, some organizations may find that multi cloud services are more appropriate. Do not think that you have a cloud computing service from a specific provider, because they will also be the best provider to meet other cloud computing needs of the organization.
Finally, in addition to conducting its own research, the organization should cooperate with experts with frameworks and experience in this field. This will help minimize any risks or challenges of adopting a cloud data warehouse and ensure that the organization gains a competitive advantage to take full advantage of the benefits it brings. "
