Role of Business Intelligence & Data Warehousing in Government Sector
There has been a drive for more efficiency and greater transparency among all the levels of the government. As a result, every department wants to analyze information using data analytics, store it using the data warehouses, and later share the public’s insights.
All this information related to historical data is also shared with the agencies clearly and concisely. For example, Budget cuts, reformations, efficiency improvements, etc., all are important challenges that governments face nowadays. BI tools help the government in taking business decisions more comfortably.
Business Intelligence and Data Warehousing can help institutions deal with this large variety of challenges. Although dashboards are created with different data analytics and data visualization tools, their purpose is to report the usage of public funds and the effectiveness of particular programs.
Business Intelligence and Data Warehousing for Public Sector
Initially, the government was not keen on investing a large amount. But, due to the advent of data analytics, data warehousing, and business intelligence BI, the government sector also started investing in the IT sector.
While the IT budget for many of those agencies has increased, efficiency remains the prominent factor for any IT project. Thinklayer provides powerful and flexible BI and Data Warehousing services that suit well to meet those requirements.
Standard and flexible reporting systems created with business intelligence tools and data warehousing services play a central role in providing emergency services at the time of any disaster. Because of this, it becomes feasible to combat any drastic situation. Also, it helps the government to identify the focus point.
Thinklayer designs dashboards with crucial features of desktop deployment that allow server support even in the event of any emergencies. Hence, after the restoration of a normal environment, more powerful, server-based reporting and analysis should become available to users again.
This type of dashboard and data warehousing services are more important in real-time when the whole world is facing the terror of the covid pandemic and severe effects of natural disasters.
Business Intelligence and Data Warehousing Applications for State and Local Government
- Educational reporting system
- Asset control and management
- Budgetary control and management
- Public expenditure disclosure dashboards
- Environmental monitoring & disaster management
Importance of Business Intelligence and Data Warehousing in Government Sector
Large stacks of data hide the solutions to the challenges of public institutions that governments have gathered throughout the years. But, Business Intelligence and Data Warehousing help them structure the raw data into meaningful insights.
This transformed data becomes more useful when converted to valuable information within an automated environment. Hence, government departments can easily find out the solutions to the nation’s problems by analyzing the patterns and trends concealed in hundreds of millions of records.
Different data warehousing tools help them to answer ad-hoc questions. Consequently, by properly studying the specific amount of data, one can create structured reports and have dashboards to follow up on their goals and actions. solutions that provide actionable insights
The data-driven experts at Thinklayer believe that efficiency improvements are a direct effect of Business Intelligence. At Thinklayer, we have prepared Business Intelligence platforms that align the realization of strategic goals within a governmental institution to their financial budget.
Also, we help government departments in optimizing their workflow by indicating bottlenecks based on analyzing data. However, by increasing insight on internal processes and their external service delivery, we bring value to the government.
We have superior technologies that generate information which is very valuable. Because of these technologies, we could create customized dashboards and data warehouses for the better working of the government sector.
Major Business Intelligence & Data Analysis Resources
Database: We have a centralized repository to store the bulk data. We use the database to keep consolidated information to avoid long waiting times when you make a query.
ETL tool: ETL stands for Extract, Transform and Load. It is the process used to get the information out of the data source like ERP, CRM, etc. Also, with the help of ETL development tools, we can make any adjustments and then make data available for the visualization tools. We can then define the transformation and then load the final information after processing the data.
Visualization tool: Once the data has been processed, the user can create graphs, charts, do additional calculations and even run complex algorithms for insightful data. These tools also provide options to share the information with others.
CASE STUDY
The Unique Identity Project by Indian Government
In recent years, international bodies like the World Bank have promoted digital identity as key to reducing fraud. It also helps in facilitating financial inclusion, enabling political empowerment, facilitating economic growth, and for many such reasons in developing countries.
A Digital Identity system includes the following components:
1) Identification
2) Authentication
3) Authorization
Because of these features, a digital identity becomes critical for the use of online services such as e-governance or e-commerce platforms. In addition, a digital identity system can be both centralized and decentralized.
Centralized Identity architectural models include state-issued electronic identity. On the other hand, decentralized identity models include identity brokers, personal identity provider models, and non-identity models.
The Unique Identity project in India (UID) is an example of a centralized identity architecture model. The Unique Identity Project in India, Aadhaar, is reported to have over one billion registrants.
It is a platform for several digital services, producing enormous troves of data precious to both the public sector and the private sector. The scheme’s objective has been to issue every resident in India a unique identification number based on an individual’s biometrics by the UIDAI, which can be authenticated and verified online.
Role of Data in Unique Identification
Various documents prepared by the UIDAI refer to the intended data sets as exponentially growing, including “data coming in from residents, vendors and partners”, and characterize this transaction data as “Big Data”.
During enrollment, the following data is collected from the individual:
- name, gender, age, date of birth
- address, email, mobile number
- details of father/mother/guardian/husband/wife,
- proof of identity/address
- iris scans, ten fingerprints
- photographs
- and if the individual wishes to link their Aadhaar number to their bank account – their bank account details.
The UIDAI does not specify the type of ‘metadata’ that is collected about and the individual during the authentication process, but at the least, it could include:
- Aadhaar number
- demographic
- biometric information of the individual
- time of authentication
- the location from where authentication took place
- entity or organization requesting the authentication
- response – yes or no.
Requesting entities will be storing and potentially sharing information associated with transactions. Thus, maintaining a DATA WAREHOUSE for their BIG DATA.
Unique Identification Integrating Databases as Big Data
In the UID scheme, data points are within the databases of service providers. These are between departments, ministries, and banks which are organized via individual Aadhaar numbers through a process known as ‘seeding.’
It is a process through which the Aadhaar numbers of residents are included in the service delivery database of service providers for enabling Aadhaar based deduplication and authentication during service delivery.
To provide services effectively, these schemes shall collect and store information through the lifecycle of an individual. The result, as we can see, is building databases on individuals, which when combined, as enabled by the Seeding process, will provide a 360-degree identification.
Promises of UID as Big Data
a) Efficient service delivery
b) Convenience for citizens
c) Better information dissemination and training
Conclusion
Thus overall, we can say that BI and Data Warehousing play an important role in the growth of a nation by supporting the government sector in many ways. And Thinklayer is always ready to provide the best data visualization and data warehouse services to the government sector.
