Dataplex: All-in-One Data Platform Tool

Streamline Data Management and Maximize Insights with Dataplex

Introduction

Data management is the process of collecting, storing, organizing, maintaining, and using data effectively and efficiently. It involves a range of activities, including data governance, data quality management, data integration, data security, and data analytics. Effective data management is critical for organizations to make informed decisions, gain insights, and stay competitive in today’s data-driven world. However, managing data effectively can be challenging, and organizations need to have the right tools, processes, and policies in place to succeed.

Dataplex is a data management solution that aims to address several challenges that organizations face when managing their data. Some of the key challenges that Dataplex can help to solve include:

1. Data silos: In many organizations, data is stored in separate silos, making it difficult to access and analyze. Dataplex provides a unified view of data, allowing organizations to easily discover and access the data they need.
2. Scalability: As organizations collect more data, it can become difficult to manage and process that data at scale. Dataplex is designed to be highly scalable, allowing organizations to easily manage and process large volumes of data.
3. Data quality: Poor data quality can lead to inaccurate insights and decisions. Dataplex includes tools for data quality monitoring and management, helping to ensure that data is accurate and reliable.
4. Data governance: As data becomes more important to organizations, it’s important to have strong data governance policies in place. Dataplex includes tools for data governance, allowing organizations to manage data access, security, and compliance.

Dataplex

GCP defines Dataplex as “Intelligent Data Fabric” — a solution that enables the organization of data lakes, marts, and warehouses by domains, facilitating the implementation of a data mesh architecture. It also provides monitoring, governance, and data management capabilities.

How Does Dataplex work?

Dataplex streamlines data management by eliminating the need for data movement or duplication and still ensuring that ownership and appropriate permissions are maintained across datasets and domains. When you add new data sources, Dataplex automatically extracts metadata for both structured and unstructured data, and applies data quality checks to ensure data integrity.

Then, all metadata is consolidated into a single, unified metastore, which is automatically updated. You can access both data and metadata using a variety of services and tools, including Google Cloud services like BigQuery, Dataproc Metastore, and Data Catalog, as well as open source tools like Apache Spark and Presto.

Under the hood, Dataplex abstracts data sources using the following terminologies:

Lake: A logical construct representing a data domain or business unit. For example, to organize data based on group usage, you can set up a lake for each department (for example, Retail, Sales, Finance).

Zone: A subdomain within a lake, which is useful to categorize data by the following:

• Stage: For example, landing, raw, curated data analytics, and curated data science.
• Usage: For example, data contract.
• Restrictions: For example, security controls and user access levels.

Zones are of two types: raw and curated.

• Raw zone: Contains data that is in its raw format and not subject to strict type-checking.
• Curated zone: Contains data that is cleaned, formatted, and ready for analytics. The data is columnar, Hive-partitioned, and stored in Parquet, Avro, Orc files, or BigQuery tables. Data undergoes type-checking- for example, to prohibit the use of CSV files because they don’t perform as well for SQL access.

Asset: Maps to data stored in either Cloud Storage or BigQuery. You can map data stored in separate Google Cloud projects as assets into a single zone.

Entity: Represents metadata for structured and semi-structured data (table) and unstructured data (fileset).

Dataplex Functionalities

Dataplex offers a wide range of functionalities to help organizations manage and govern their data assets effectively. Some of the key functionalities include:

1. Intelligent Data Fabric

As mentioned, Dataplex provides an intelligent data fabric that allows organizations to organize their data lakes, marts, and warehouses by domains. This enables the implementation of a data mesh architecture, which allows for greater flexibility and scalability in managing data assets.

2. Data Governance

From Dataplex, access control via IAM can be granted on to assets manage by Dataplex.

3. Data Catalog

Dataplex includes a data catalog that acts as a one-stop shop for all the data discovery, understanding, and looking needs across the organization.

4. Data Lineage

Data Lineage helps tracking the origin and movement of data across the organization. This helps to ensure that data is accurate, complete, and consistent.

5. Business Glossary

The Business Glossary provides a single place to maintain and manage business-related terminology and definitions across the organization. It lets you attach the terms to the columns of cataloged data entries.

6. Data Profiling, Data Quality and Monitoring

Dataplex offer an automatic data profiling scan to discover useful summaries about the organization’s data. This in turn adds value to Dataplex Data quality to ensure data accuracy, completeness, and consistent consistency. Data quality can be used in tandem with GCP Cloud Monitoring to provide real-time monitoring of data assets, enabling organizations to detect and respond to issues quickly.

Overall, Dataplex offers a comprehensive set of functionalities that enable organizations to manage and govern their data assets effectively. By providing a unified view of data assets, ensuring data quality and security, and enabling data analytics, Dataplex helps organizations to make better use of their data and gain a competitive advantage.

Benefits of Dataplex

With Dataplex, organizations can manage data across multiple silos from a single pane without the need for data movement. Additionally, Dataplex enables the following benefits:

• Seamless integrate with the rest of GCP toolset Cloud Storage, BigQuery, Dataproc, Dataflow, Data Fusion, GCP’s Notebooks,…
• Integration with open-source tools such as Apache Spark, HiveQL or Presto.
• Auto-scale to fit the data needs of the organization without requiring any additional infrastructure or resources.
• Centralized metadata management and cataloging allowing easy browsing, searching, and discover relevant data to empower analytical works and data-driven business decisions.
• Enforce centralized and consistent data controls across the data sources within Dataplex Lake at scale.
• Without the need to move data around, data sources still can be logically organized into business-specific domain in a cost-efficient manner.

Challenges of Using Dataplex

While Dataplex offers a wide range of benefits for the organization, it is important to also consider some of the potential challenges of the tool.

• Dataplex does not offer integration with different major cloud platforms like AWS or Azure nor on-prem one. This is a major drawback preventing large organizations who are using multi-cloud and/or a hybrid cloud model to adopt Dataplex. Furthemore, current release of Dataplex only offer Big Query and Cloud Storage as source for its assets.
• Data Quality checks offered by Dataplex is quite rudimental and does not accommodate for complex or dynamic data quality controls.
• Data issue alerts, while possible to set using GCP Dataplex Data Quality and Cloud monitoring, may not provide users with complete information on the issue at hand. Additionally, a custom solution may be required to summarize data quality issues and redirect users back to Dataplex to investigate and take appropriate action.
• Dataplex is relatively new and still in development, thus, its functionality is still being fixed and updated frequently. Consequently, Infrastructure as Code tool like Terraform doesn’t fully support GCP Dataplex.

Conclusion

By uniting data view, automating data management tasks, and enabling collaboration among data teams, Dataplex can help organization streamlinetheir data management processes and make better use of their data assets. Overall, despite its limitations, Dataplex remains a powerful tool for organizations looking to leverage the power of the GCP ecosystem for their data management needs.