Data Exploration | Tom Sawyer Software

Tom Sawyer Explorations is a graph intelligence application that empowers analysts to rapidly uncover insights through data integration, graph pattern matching, and advanced graph visualizations and analysis—all without any coding and without having to know query languages.

Data professionals of all levels can easily connect to a graph database and construct a database query without needing advanced coding skills or knowledge of the Gremlin or Cypher query languages. Explorations automatically returns the query results in an interactive visualization of the relationships between elements meeting the search criteria and provides built-in graph analysis algorithms enabling a deeper understanding of the complex relationships within the data.

No matter your level of technical knowledge, Tom Sawyer Explorations provides the data discovery tools you need to efficiently generate actionable insights.

Watch this short introduction to Explorations to see how it enables data exploration and can help uncover insights in minutes, with no coding.

Explorations 1.1 Available Now

The latest release of Tom Sawyer Explorations enhances our no-code platform and analysts' data exploration workflow with robust new features designed to streamline and secure the analysis experience.

Designed for data analysts

Tom Sawyer Explorations is tailored for analysts and data professionals across various industries. Whether you're working in finance, healthcare, cybersecurity, or any field that requires deep data analysis, Explorations offers powerful exploration tools to enhance your data exploration and decision-making processes without the need to know database query languages.

Use cases benefiting from data exploration solutions

Explorations addresses critical data exploration needs across various applications, transforming how data is analyzed and utilized.

Financial Fraud Detection: Identify suspicious activities and hidden connections within vast financial data to prevent fraud and ensure compliance.
Patient Data Analysis in Healthcare: Analyze patient records and medical histories to uncover data trends and patterns that can lead to better diagnosis and treatment plans.
Network Security Threat Identification: Detect potential security threats by mapping and analyzing network data to find vulnerabilities and prevent cyber-attacks.
Social Network Analysis: Understand social structures and influence by visualizing relationships and interactions within social networks.
Supply Chain Management: Optimize supply chain operations by analyzing data to find inefficiencies, predict demand, and improve logistics.

Tom Sawyer Explorations provides data techniques that can help optimize supply chains.

Industry-specific benefits of data exploration solutions

Explorations brings significant benefits to a wide range of industries by enhancing data visualization and analysis capabilities.

Finance: Enhance risk management, compliance, and fraud detection with advanced graph analytics.
Healthcare: Improve patient outcomes through detailed analysis of medical data, uncovering critical insights for better care.
Cybersecurity: Strengthen defenses by visualizing and analyzing network data to identify and mitigate potential threats.
Telecommunications: Optimize network performance and customer service by understanding complex communication data.
Logistics: Streamline operations, predict demand, and enhance supply chain efficiency through comprehensive data analysis.

Tom Sawyer Explorations brings significant benefits to a wide range of industries.

Powerful exploration tools for exploring data sets

Explorations offers tools that facilitate the data exploration process. Analysts are free to perform data examination investigations and interact with their data to achieve insights with this no-code platform.

Seamless Data Ingestion

Support for popular graph databases with one-click data mining.

Visual Schema Interaction

Interactive graph visualization to selectively choose which schema elements to visualize.

Interactive Data Views

User-friendly, interactive graph drawing and inspector views that enable data exploration of connected data points.

Customizable Graph Aesthetics

Attribute-based node color and text for customized visualizations.

Advanced Graph Analysis

Built-in graph analysis algorithms for identifying patterns, trends, and anomalies.

Secure and Scalable Deployment

Flexibly deployment options that fit into your existing IT infrastructure.

Connect to these popular graph databases for efficient data exploration

Tom Sawyer Explorations simplifies the data connection process, providing a foundation for exploring data sets and performing in-depth analysis.

Easily connect to your preferred graph database to support your specific data exploration use case. Supported databases include Neo4j, Neptune Gremlin, Neptune openCypher, JanusGraph, OrientDB, and Cosmos DB.

Tips when starting your data evaluation journey

Starting your data evaluation journey can be overwhelming, but with the right approach, you can gain valuable insights efficiently. Here are some essential tips to guide you through the process, ensuring that your analysis is effective and impactful. From defining clear objectives to maintaining data quality and documenting your methods, these steps will set a solid foundation for your data exploration efforts.

Define your objectives

Clearly outline your goals, whether it's understanding customer behavior, identifying trends, or optimizing processes. Establishing specific, measurable, achievable, relevant, and time-bound (SMART) objectives will help you focus your efforts and tailor your analysis methods accordingly. By having well-defined objectives, you can avoid unnecessary data collection and analysis, saving time and resources.

Ensure data quality

Invest time in cleaning and preparing your dataset—remove duplicates, handle missing values, and standardize formats. Establish validation rules and automate quality checks to ensure data consistency. By proactively managing data quality, you minimize errors and build a robust dataset that supports accurate and actionable insights.

Know your data

Before preparing your data for analysis, familiarize yourself with the dataset by exploring its structure, contents, and patterns and identifying outliers or anomalies. Understand the context behind your data—know the sources, the timeframe, and the methods used for data collection. A thorough understanding of your data's origins and limitations ensures that your analysis accounts for potential biases and inaccuracies.

Begin with a small sample

Begin with a small sample to understand the structure and test your methods. This allows you to refine your approach and adjust your tools without consuming excessive resources. Once you validate your process, scale up to the full dataset for a comprehensive analysis.

Document processes

Document your steps, such as how you cleaned the data, transformed variables, or applied algorithms. Include notes on challenges faced and how they were addressed. This practice not only provides a reference for future projects but also helps communicate your approach to stakeholders and collaborators, promoting a culture of transparency and trust.

Iterate and refine

As you explore, you might uncover new questions or insights that prompt you to revisit and refine your approach. Continuously assess your objectives and methods to adapt to new findings and emerging patterns. Iteration helps improve the accuracy and depth of your analysis over time.

Achieve first data visualization in three simple steps

Connecting to your graph database and getting your first data visualizations is made simple with Explorations. Simply connect to your database and select the schema elements and connections you want to view.

In just two clicks, Explorations automatically generates the query based on the schema elements you choose, displaying it in an easily understandable graph drawing. When you execute the query, Explorations displays the results of the data query in an interactive graph data visualization.

1. Select Data Source

Select the type of graph database containing your data.

2. Enter Connection Details

Enter the database connection details to connect to your graph database.

3. Visualize and Explore Data

Choose the schema model elements you want to visualize, and click Run Query.

Visually interact with your schema

There are several variables to consider when it comes to data profiling and exploration. In addition to variables such as the type of database in which your data resides and the data quality and volume, having an understanding of the structure of the schema and cutting through the noise is paramount when performing an exploratory data analysis.

With Explorations' schema viewer, you can focus on the relevant parts of your schema using an interactive graph visualization. The schema viewer provides a high-level view of the schema structure, showing the relationships between schema model element types and the count of each model element type.

In the schema viewer, selectively visualize what matters most by simply selecting the model element types and relationships you care about. Ignoring the data you don't need, will remove unnecessary noise boosting efficiency and insight extraction.

See the structure of your graph database and selectively visualize what matters with Exploration's schema viewer.

See the structure of your graph database and selectively visualize what matters with Exploration's schema viewer.

Effortlessly construct no-code database queries for data analysis

Quickly uncover insights and effortlessly explore data, without the need to know Gremlin or Cypher query languages.

With the no-code, pattern-matching Query Builder, construct your database search to find graph patterns through an intuitive graph visualization. Easily apply conditions to your queries so you can hone in on the elements of interest.

When you run the query, Explorations automatically returns the results in a visualization of the relationships between elements meeting your search criteria.

The pattern-matching Query Builder leverages an intuitive graph visualization, allowing you to explore and identify graph patterns effortlessly.

Interactively explore relationships to refine your data investigation

With Explorations, you can delete elements from the graph, filter out elements, and automatically load data directly into the graph drawing with the load neighbors feature.

And our automated graph layout quickly cleans up the visualization for overlap-free drawings.

Selectively load elements into the graph drawing to expand your investigation.

Gain data insights with data attributes and criteria selection

With Explorations' user-friendly, interactive graph drawing and inspector views, you can quickly see the data attributes of individual elements.

You can also explore connected data points with intuitive criteria selection, deepening your understanding of complex relationships within your data.

Select elements in the graph drawing to visualize their attributes.

Accelerate your data investigations with synchronized tables

Accelerate your investigation experience with a table view. Add and customize as many tables as needed, selecting element types, attributes, and column order to suit your analysis.

Tables are searchable and synchronized with the drawing view, offering the flexibility and control needed for a seamless and efficient exploration experience.

Table views are searchable and synchronized with the drawing view to enhance the data investigation experience.

Enhance data visualizations with customizable graph aesthetics

Augment your graph drawings to aid in comprehension and provide additional insight to domain experts and stakeholders.

Add attribute-based node color and text to highlight key information, providing data insights that are visually compelling.

Attribute-based node color and text highlights key information, providing data insights that are visually compelling.

Powerful graph analytics at your fingertips

Leverage built-in graph analysis algorithms to uncover data trends, understand network dynamics, and make informed decisions.

Explorations includes a set of social network analysis algorithms that rank based on an importance factor determined by each technique. These algorithms are useful techniques for social network analysis and help reveal important elements in the graph.

Supported algorithms include: Betweenness, Closeness, Degree, Eigenvector, and PageRank.

Learn more about graph analysis here.

Social network analysis ranks elements based on importance to reveal key elements in the graph.

Social network analysis ranks elements based on importance to reveal key elements in the graph.

Discover natural clusters in your data

Also included is clustering analysis that finds different types of natural clusters—or groups—in the topology of a graph.

Clustering is a useful technique for operations and enterprise architecture management.

Clustering analysis finds natural groupings in your data providing additional insight.

Apply analytics to uncover fraud

See how Explorations can quickly uncover hidden patterns, expose fraud networks, and navigate complex financial relationships by applying advanced graph intelligence.

Uncover hidden patterns and expose fraud networks with Tom Sawyer Explorations.

Create and manage data explorations for a streamlined experience

Ability to manage individual data exploration projects keeps users focused on analysis. Add new projects and Explorations auto-saves database connections, loaded elements, styling, filters, and active analysis algorithms allowing you to effortlessly pick up right where you left off without any worry of losing progress.

Manage your data explorations and effortlessly pick up right where you left off.

Secure and scalable purchasing and deployment options

Explorations can be quickly and securely deployed on-premises or in the cloud, ensuring integration into your tech stack is made easy.

Explorations also provides secure access with integrated authentication options that align with your existing IT infrastructure.

On-premises

Effortlessly deploy Tom Sawyer Explorations using container technologies like Docker and orchestration via CloudFormation or Terraform for a scalable and repeatable setup. Start your free trial today.

Cloud

Explorations is available for a free 5-day trial in AWS Marketplace. Host your application on an AWS EC2 instance in any region. Take advantage of flexible usage-based pricing, and scale up and down or turn on and off as needed.