Post：2020/06/01
Nowadays, data analysis has become the lifeblood of IT. More and more enterprises or institutions actively embrace big data, machine learning and other technologies, hoping to dig the huge value, optimize decision-making basis, and accelerate the digital transformation. However, it cannot be denied that data analysis is a huge project. From the acquisition, cleaning, management, modeling and visualization of data, to the linkage to the prosperous API economy, each link contains a considerable technical content.
IISI, a professional, large-scale and international information and communication service benchmarking company, foresaw the irresistible trend of big data many years ago. It set up a data service team. After long-term technical research and development and project experience accumulation, IISI has gathered a complete service capacity sufficient to help enterprises or institutions to build modern data analysis infrastructure and accelerate the landing of big data and AI application.
Accelerate to meet the needs of customization with independent R & D energy
IISI started data service in 2011, when the market focus was on business intelligence (BI). It participated in the tax reconstruction plan of the Ministry of Finance, during which it was responsible for the establishment of a high-level executive decision support system, and assisted the Ministry of Finance to build the ability of tax impact analysis. This experience enabled IISI to open the door to the operation of data projects.
By 2013, big data issues continued to prosper, with needs of related project gradually released by both government departments and private enterprises. Determining that big data was the trend of the times and it was necessary to preemptively make the layout at the beginning of the market, IISI set up a data service team. Mr. Jeff Mau, Deputy General Manager of IISI Government and Finance Business Department, stressed that in the era of information as the king, the one who owns the data will own the market. So whether looking back at the past decade or looking forward to the next decade, the trend of data analysis will not be out of fashion, and will be closely related to the trend of AI and IOT. IISI has participated in many related projects and processed different types of data, so it has the capability to compete for business opportunities.
Jeff Mau said that with the maturity of service architecture, IISI has now classified its data services into five categories, including data warehouse construction, data integration (ETL), data analysis, visualization and related hardware and software sales. In other words, from data collection to data warehouse construction, modeling, analysis, prediction, to the final BI visual report presentation, or provision of services through API, they are all in the IISI end-to-end service category.
Edison Hsu, manager of IISI big data team who has led several successful data service projects, pointed out that there are corresponding technical tools for different project stages mentioned above. Because the Company has a wide and deep range of business involvement, on the one hand, it can use the tools specified by the customer; on the other hand, if the customer does not specify the tools, it can assist in selecting the most suitable commercial or open-source tools according to the current situation and needs of customers, such as Vertica in data warehousing, Trinity, Data Stage or Pentaho in ETL, and Tableau or Cognos in visualization.
In terms of data analysis, IISI is mainly to assist users in developing R or Python programs. However, with the advent of the cloud era, the company also follows the layout steps of customers, and uses R / Python programs required by public cloud environment development projects such as AWS SegeMaker to accelerate the completion of data analysis process by combining with public cloud storage services. In addition, IISI signed a VAR distribution contract with Kong last year (2019) to introduce the “Kong Enterprise "API management software (APIM) to Taiwan to help users establish data service gateways.
In the meantime, IISI also shows its independent R & D energy, and has successively bred iML (automated machine learning tool), Tableau customized entry platform, simulation data production module, DigiSight (an IoT platform) and IISI ChatBotManager (Chatbot software), etc.
"Although there are solutions in the market similar to AutoML, IoT or ChatBot, IISI has a unique advantage by using self-developed modules." said Edison. Many large and medium-sized enterprises tend to keep customization space, rather than take all the existing products as they were without making any changes. Therefore, they rely heavily on the logistics support ability of suppliers. IISI, which has a niche such as independence and localization, can quickly meet the customized needs of users without the need to wait for the support of overseas manufacturers, and thus could easily win the favor of customers.
Manufacture simulation data and start the government cloud application
Jeff Mau stressed that IISI's data service development strategy not only looks at the historical track, but also plans ahead of time, aiming at some forward-looking and differentiated products. Generally speaking, it follows two major development directions: one is to develop value-added components on the shoulders of giants, such as Tableau, and the other is to develop its own products to shape its sustainable competitiveness.
The target customer groups of data services are in three major areas, namely government agencies, financial institutions and mobile service industries (such as automobile industry). Among them, the motivation of introducing data services in finance, automobile and other industries is similar in that they need to turn from being passive to proactive in response to trend of digital transformation and explore potential customers by means of precision marketing and personalized publicity, instead of waiting for customers to enter the business premises. As for government agencies which shoulder the policy mission of building an intelligent government, they need to create cross domain integrated data warehouse to facilitate the checking of all kinds of data and production of analysis results on various issues and further improve the quality of policy decision-making.
When it comes to the classic cases of information services, IISI believes that its participation in the big data project of the Ministry of the Interior can be regarded as one of the indicator cases worth sharing. In 2018, the company assisted the Statistics Department of the Ministry of the Interior to import the data value creation methodology, and developed SOP processes from the four aspects including "topic setting", "data inventory", "data cleaning" and "data analysis", so as to help the Statistics Department of the Ministry of Interior to implement big data analysis according to the standard procedures. In 2020, in order to make government data available to the industry and schools without concerns about information security, IISI helped the Statistics Department of the Ministry of the Interior to produce simulation data of Taiwan's population, uploaded the simulation data to AWS S3, and then provided a SageMaker environment for the use of teams and schools participating in the MOI Data Innovation Application Compitition. According to the distribution basis consistent with the parent data, the environment creates innovative application services and becomes the pioneer of government cloud application.
Looking forward to the future, IISI will gradually lay out relevant solutions for data governance, data virtualization, logical data warehousing, precision marketing, etc., in the mode of independent R&D or agent distribution, so as to strengthen its data services.