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Empowering Education and Career Decisions Through Comprehensive DataEmpowering Education and Career Decisions Through Comprehensive Data

Education Data – More Than Just Test Scores

Data is one of the most powerful tools available for individuals along their education and career journeys. It’s more than just test scores, and it covers a broad range of topics. Academic, testing, and assessment data, educator data, demographic data, individual-specific data, climate and culture data, and fiscal data all play an important role in education.

Academic Information

Data on student academic achievement and trends from the National Center for Education Statistics. Includes PK-12 educational information services, the Integrated Postsecondary Education Data System, college and university information systems, and student financial aid data.

Academic information goes beyond test scores and focuses on the experiences and conditions of students and educators in the learning environment. New York State Education Department’s commitment to open and machine-readable data is supported by this site which offers a range of academic information.

Testing and Assessment Data

Students and educators need access to comprehensive data that goes beyond test scores. When individuals, families, teachers, communities, and policymakers have the right information for their roles, they can make informed decisions that support learners from early education through the workforce.

This site provides access to state assessment data for grades 3-8. It also includes disaggregated files displaying results for specific groups of students, as well as trend information.

Integrated Postsecondary Education Data System (IPEDS) provides aggregated-level data submitted by higher education institutions in 12 interrelated survey components about general higher education topics.

Educator Data

Data is one of the most powerful tools to support individuals along their education and workforce journeys. Students, families, educators and policymakers all need access to comprehensive data that empowers them to make informed decisions for their roles.

Find educator-related data including salary, certification and highly qualified status. Also find information on the state’s public school districts, schools and campuses. Data includes academic information, testing and assessment data and demographics. Search by keyword or explore the data visualizations, resources for the classroom and applications created from open data.

Demographic Data

Data on students and educators that help paint a full picture of the state of education, including discipline and climate and culture data. Additionally, fiscal data shows how schools and districts are funded and what they are spending.

Contains data on school and student outcomes, such as student achievement, graduation rates, and college completion rates. It also includes information on school finances and budgets, teacher salaries, and student loan and workforce data. Various data sets are available in both machine-readable formats and Excel spreadsheets.

Individual-Specific Data

Students, parents, educators, and community members need comprehensive data in order to make informed decisions that support learners through their educational journey. Open data empowers entrepreneurs and innovators to create solutions that drive innovation in education.

To meet the information needs of the public, CDE makes available several types of data in various formats. For example, the Performance Framework Resources page provides spreadsheets of current and historical performance framework data.

Individual-level data, including student counts of 16 or more and school system and teacher count of 5 or more, are suppressed in response to requests to ensure that PII is not disclosed. See our Non-Confidential Data Request Form for more information.

Climate and Culture Data

School culture and climate are critical to the success of students. When students and teachers are safe, supported, and engaged, their academic performance improves. But school environments are complex.

A comprehensive, research-based school climate survey can help district leaders measure and monitor progress towards a positive culture and climate. When paired with a powerful data analysis tool, these surveys can quickly inform school improvement plans (SIPs). Seek out a holistic solution that can automatically seek out this critical data and provide a streamlined path for its interpretation.

Fiscal Data

Fiscal data reveals how schools and districts are funded. This includes per-pupil expenditure information, as well as federal and state funding levels.

The Federal Student Aid Data Center is a centralized source of information regarding the Title IV financial assistance programs. It provides student aid data, lender and guaranty agency reports, and business information resources.

America’s finances are made up of money coming in (revenue) and money going out (spending). Explore revenue sources, spending categories, trends over time, and the national debt.

Postsecondary and Workforce Data

A wide range of people need comprehensive data to make informed decisions that support education and workforce goals. These include students, families, educators and policymakers.

A key goal of SLDS and Workforce Data Quality Initiative (WDQI) grantees is to create longitudinal data systems that connect information from pre-K, K-12, postsecondary education and the workforce. GAO analyzed data from a 2013 survey of SLDS and WDQI grantees on their ability to match individual records between these sectors. GAO also reviewed examples of how states use these systems.

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Databases: Relational, Object-Oriented, Hybrid, and GraphDatabases: Relational, Object-Oriented, Hybrid, and Graph

The Top 3 Databases

A database is a collection of searchable information. It is usually a more credible source than Google because it contains scholarly articles and journals.

A database can store data in various formats. Choosing the right one for your needs is critical to ensure a high level of performance, scalability, and agility.


Relational databases are the traditional choice for structured data. They feature data abstraction, separating the database schema from its physical implementation. This allows developers to change the database structure without affecting applications that depend on it, promoting flexibility and reduces maintenance efforts.

They are also good at displaying complex relationships among data in multiple tables. This is accomplished by linking information using unique identifiers called keys. These identifiers are assigned to records contained in one table and then included in records of another table when they have a relationship to the first record. This creates what is known as a foreign key.

These relationships are stored in a table called a relation instance. Each relation instance is populated with tuples that conform to the blueprint set forth by the database schema. The tuples are then grouped into rows and columns. The relational model is excellent at maintaining data consistency across applications and database copies, which are known as instances.


An object-oriented database stores information in objects, rather than in tables like a relational database. This enables more complex relationships, inheritance, and other features. It also allows for encapsulation, where methods and data are hidden from outside programs. Object databases are more efficient than traditional databases and are often used for storing multimedia data, such as text, sound, video, or graphics.

They also support user-constructed data types. This is important for applications that require a large variety of interconnected data. These databases are often used in the library sector and by healthcare organizations to store, track, and retrieve CAT scans, X-rays, electrocardiograms, and other forms of medical data.

Object-oriented databases are a good choice for projects that need to store and manage complex, interconnected data. However, they can be more difficult to learn and use than SQL, which is the standardized query language for most relational databases. This can increase development and maintenance costs. Another disadvantage is that they are less compatible with relational systems and other databases.


As a business grows, it becomes necessary to consolidate data from various sources. For example, customer transaction data can be consolidated from online platforms, point-of-sale systems, and CRM tools. This enables organizations to gain valuable insights into customer behavior and preferences. Moreover, it helps them optimize operational processes and drive growth.

Hybrid databases provide scalability and flexibility. They use both relational and NoSQL database technologies and can scale horizontally by distributing data across multiple servers or vertically by adding more resources to a single server. This feature provides businesses with more flexibility when developing software and updating existing applications.

Furthermore, hybrid databases support data and workload portability between different private and public cloud environments. This is a vital feature for avoiding vendor lock-in and achieving cost and efficiency benefits. In addition, it can help organizations avoid the risk of losing their valuable data. It also makes disaster recovery easier and more effective. This feature is especially important for businesses that operate in IoT environments.


Graph databases are designed to store collections of data without a fixed schema and to be linked together by relationships. They use special algorithms to simplify and speed up complex data queries. These features make them an ideal choice for applications that need to navigate through a large number of interconnected data.

Graph Databases offer a flexible way to represent and visualize data in a more natural and intuitive manner, improving query performance and driving value like never before. They also provide a more agile and faster process for modeling complex relationships, even when the dataset is extremely large.

They are a great fit for many applications, such as e-commerce recommendation engines that link click histories and social channels to customer profiles, or for fraud detection and analysis. However, they are not appropriate for transactional data, which requires a strict table structure and predefined fields. They are also not suitable for applications that need to respond to multi-faceted commands, such as “list all clients who have an income over $200K between the ages of 20 and 40.” For these types of applications, a relational database is the better option.

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Protecting Personal Data in Education: Importance, Regulations, and ComplianceProtecting Personal Data in Education: Importance, Regulations, and Compliance

Data Protection in Education

School records often contain a great deal of personal information about pupils and staff. These must be protected to avoid the damage that could result from their loss or unauthorised access.

This is why the importance of following data protection procedure needs to be re-communicated to teachers. However, these procedures can sometimes be compromised by cyber-attacks or unmanaged devices.


The UK GDPR is a set of rules that governs the protection of personal data in the United Kingdom. It is similar to the EU GDPR, but it also contains additional restrictions and derogations. This makes it a very important piece of legislation for education institutions, which must follow strict guidelines when handling student and staff data.

The law requires schools to have a lawful basis for processing data, meaning that they must explain all procedures to individuals before collecting their information. They must also use the data for pre-stated purposes and time periods. Additionally, they must adhere to all UK GDPR regulations.

Schools often handle what the UK GDPR classifies as’special category data’, which includes pupil information such as ethnicity and race. This data must be carefully protected, and the school must ensure that it has various data protection protocols in place. The ICO is required to produce four statutory codes of practice under the UK GDPR: age appropriate design, data sharing, direct marketing, and journalism.

Personal information

In general, personal data refers to anything that can be used to identify a living person. This includes names, email addresses, images of people, ID numbers, financial information and health records. There is also a separate category of data called ‘sensitive personal information’, which requires extra protection.

Schools hold a great deal of personal information relating to staff, pupils and parents. The security of this data is a priority as a breach could have serious consequences for the individual concerned. All manual and digital records are required to be secured with a level of protection that reflects the potential harm that could occur if the information was lost or misused.

Schools must also be transparent about the personal information they hold on individuals. They must explain why the information is collected and have processes in place to correct any inaccuracies quickly. In addition, they must limit the storage of personal information to the minimum necessary for the purposes for which it is processed.


Schools work with a large amount of personal data – including pupil names, addresses and medical information. They also store information about staff, job applicants and governors. It is vital that this data is secure to protect the individuals involved. A breach of data can cause severe damage to people’s lives and also a school’s reputation.

Schools should consider the use of security systems like encryption and shredding physical copies of paper documents containing personal information. They should also install virus-checking software and turn off auto-complete settings on computers. Small electronic storage devices like memory sticks should be locked away securely and password protected when not in use.

Attending a PECB Certified Data Protection Officer training course is an excellent way to acquire the skills and knowledge needed to act as a DPO for your organisation. Upon completion, you will be able to advise your organisation on how to meet its data protection obligations. The training is interactive and involves both theory and best practices.


Schools store a lot of personal data, from student PII and research IP to confidential grant applications. This means that they are particularly vulnerable to data breaches and must take extra precautions to ensure that all staff follow strict data protection procedures.

Fortunately, there are tools available to help with compliance. For example, security solutions like Endpoint Protector can allow educational institutions to track any attempts to transfer data onto USB devices and flag any suspicious activity. This allows educational institutions to be proactive about data security and create a culture of privacy in their workplace.

The GDPR requires that schools have a data protection officer (DPO) to oversee the school’s data processing activities. The DPO must be knowledgeable about the school’s data and how it is used, as well as GDPR requirements. DPOs must also communicate with data subjects regarding their rights and how the school uses their information. This includes the right to correct personal information, opt out of targeted advertising or data sales, and request the deletion of their data.

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