Why Businesses Should Use a Graph Database

Why Businesses Should Use a Graph Database Large volumes of data produced by businesses can be cleaned and structured data generated with the help of data cleansing services. A graph database is more flexible and has many more advantages than a traditional relational database.

www.managedoutsource.com

MOS Managed Outsource Solutions (800) 670 2809 8596 E. 101st Street, Suite H Tulsa, OK 74133

The ability to analyze and act on data is very important for any business. The data can be used to measure a wide range of business activities both externally and internally.

These data help to understand the market condition, customers, save cost and improve productivity. The data can be structured or unstructured; so, before the data can be used for analysis it needs to be cleaned. Businesses can use data cleansing services to clean all data and derive useful results. Clean and structured data can be used to create graphs to visualize data and comprehend statistics.

This helps to assess business

performance, understand financial reports, relationship among variables from profit to loss to sales and marketing figures.

Graph Database Ideal for Businesses Today, organizations use graph database for faster batch processing and gaining business insights. Graph Database is a simple NoSQL database alternative to a traditional relational database. Today, businesses must not only manage huge volumes of data, they must also create insight from existing data. That makes relationships between data points more important than the individual points themselves. Since the graph database stores relationship information as a first-class entity, it is more useful for businesses. Unlike the less flexible traditional relational database systems, graph databases are flexible, can easily expand a data model and conform to changing business requirements.

It helps to analyze complex data relationships and gives organizations greater ability to move reporting into a real time or near real time mode. It is widely used in almost all industries

such

as

life

sciences,

healthcare,

financial

service,

government

and

intelligence. It allows visibility across the datasets, enabling organizations to share data and see how it is connected. This online database management system features CRUD (Create, Read, Update and Delete) operations working on a graph data model. Since relationships take priority in graph databases, your applications don’t have to deduce data connections. The data model for a graph database is considerable simpler and more expressive than those of relational or other NoSQL databases.

Ryan Boyd, head of developer relations North America for Neo4j, a graph database solutions provider says that •

Financial services companies are using graph databases to discover instances of both internal and external fraud.

•

The retail sector is using the technology to assist them with purchase recommendations for customers.

•

In logistics, graph databases are utilized to plan package routings

www.managedoutsource.com

(800) 670 2809

•

In networking and IT, the technology is used in root cause analysis.

The graph database is significant for data analysts from the point of view of Big Data because it advances the case for real-time analytics and has the capability to investigate into complex data relationships.

Ensuring Flexibility and Security for Graph Database Businesses can surely benefit from the flexibility of graph databases, it is important however, to ensure security as well, a feature of traditional relational databases. This security is guaranteed by AllegroGraph, a Triple Attributes solution created by Franz Inc, an early innovator in Artificial Intelligence and leading supplier of Semantic Graph Database technology. It is a unique feature that provides power and flexibility to address high security data environments like HIPAA access controls, security models for policing, intelligence and government and privacy rules for banks. AllegroGraph Triple Attributes assures security and is easy to use. It provides more expressiveness than security methods in relational databases or property graph databases and prevents performance degradation. It allows data to be revealed to users based on roles. It combines the linking and discovery power of graph databases with the security of need-to-know access. It enables HIPAA compliance for the healthcare industry; helps implement the privacy rule for the financial sector, as well as models and policies for the government for classified information.

Data is stored in the W3C standard based on Resource Description Framework, also called triples. It provides metadata for each individual triple and uses of Triple Attributes are date, time, weight, security level, classification level, trust level and provenance information. These attributes can be accessed in queries and graph algorithms and greatly increase the power of graph-based applications.

The Triple Attribute feature was introduced for governments’ data security. It can be implemented for diverse data analytics domains as AI truth maintenance systems, and atmospheric observations to understand real-world events such as crop yields clearly. It can be also used for storing block chain hashes and ICO public keys for KYC applications and analytics.

Tribute Attribute Security is available in AllegroGraph v6.3 and includes: •

Supports forXQuery and XPath math functions

•

CORS (Cross Origin Resource Sharing) support

www.managedoutsource.com

(800) 670 2809

•

Improvements and new feature in AGWebView, including the ability to add data by pasting in text area, new report dialogs which detail storage usage and other things, and a new index management page.

•

The Magic Properties feature allows connecting from SPARQL to other databases, machine learning tools and programming languages that provides a highly enriched application query environment.

The key advantages of graph databases are: •

Improved performance

•

Greater flexibility

•

Agility

A graph database will help businesses to connect their data in meaningful ways to address problems within the organization and enable new business opportunities providing business value and growth. It helps collect data insights and predictive analytics from complex data, insights that may not be revealed with conventional databases.

For any business to implement a graph database, it should have accurate and structured data. Large volumes of data generated by businesses can be cleaned, and structured data generated with the help of data cleansing services.

www.managedoutsource.com

(800) 670 2809