August 2023 Summaries

Amazon's advertising platform offers numerous targeting options to reach potential customers, including keyword, product, interest-based, demographic, and audience lookalike targeting. These capabilities allow advertisers to capture the attention of consumers actively seeking related products or those already inclined towards their offerings. Amazon Advertising also provides a range of advertising solutions, such as sponsored products, sponsored brands, sponsored display, stores, and an Amazon Demand Side Platform (DSP). Additionally, integrating data from Amazon Advertising into a centralized data warehouse using tools like CData Virtuality enables in-depth long-term trend analysis, simplifies data integration with other business information, and maximizes flexibility in choosing analytics tools.

CData Virtuality has introduced several new features to enhance its SaaS experience, including Cloud Agent, OData connection for Tableau and Salesforce, and improved onboarding through Stonly Integration. The Cloud Agent bridges the gap between on-premises data sources and CData Virtuality SaaS, enabling seamless cross-network communication, enhanced security, and a user-friendly setup process. The new OData connection enables users to connect directly with Tableau and Salesforce, providing real-time analytics and streamlined data integration. Additionally, Stonly Integration has improved the onboarding experience, offering a tailored onboarding process, easier and faster onboarding, and a smooth learning curve for colleagues with different roles and technical skill levels. CData Virtuality's security measures have also been fortified, earning prestigious certifications such as SOC 2 Type 2, SOC 3, and HIPAA compliance. The company invites users to experience the future of data virtualization with its 30-day free trial.

Workday is a popular SaaS human resources and financial management tool that offers flexibility, but can be challenging to integrate into existing processes due to its customizability. To overcome integration challenges, organizations should focus on native connections to application platforms rather than bolt-on integrations. Additionally, leveraging analytics tools like CData Workday Drivers provides seamless access to Workday data from popular analytics tools like Microsoft Power BI and Tableau, while also enabling data management and storage through solid connections between applications systems. This can help organizations manage and store data confidently, replicate Workday data into a central repository, and connect Workday to their favorite tools for efficient integration.

The CData Product team has released its Summer 2023 update for CData Sync, focusing on enterprise features that offer more granular control over implementations and speed deployment. The new release introduces a "Job Creator" role with enhanced role-based access control, allowing administrators to restrict user actions and improve security. Additionally, the feature set includes cloning connections, tags and filters, a transformation library, IBM Db2 native driver support, enhanced history mode for change data capture, merge functionality in Google BigQuery, Kafka history mode, and business views that enable curated data sets for business reports and metrics. These updates aim to simplify setup, improve control, and enhance the overall user experience.

CData is a sponsor of the upcoming Workday Rising conference, which offers expert-led sessions and innovations for planning, HR, and finance challenges. Attendees can choose from hundreds of sessions to learn about their industry and role, share insights with other customers, and get hands-on experience with Workday data. CData provides a hassle-free way to connect Workday to popular tools like Power BI, Excel, Tableau, and more, making it easy to query live Workday data within these tools. By connecting Workday to your favorite analytics tools, you can capitalize on your investment and make well-informed decisions that affect your business. The conference is a great opportunity to discover how to integrate Workday with the rest of your tech stack.

The concept of data gravity refers to the phenomenon where large datasets attract more apps, services, and data, resulting in an unrelenting cycle of growth. This has significant implications for organizations, including data management challenges, increased complexity, and potential latency issues. As a result, managing data gravity is crucial to ensure timely access to and analysis of data, which is critical for informed business operations and strategies.

CData Connect Cloud offers a new approach to data virtualization for the cloud, providing a fully managed SaaS solution that builds a logical data layer from hundreds of popular SaaS applications and cloud data sources within an easy-to-use, centralized platform. This approach simplifies various data formats into a tabular model and uses dynamic metadata discovery to provide information about data structure, attributes, and characteristics, making it easy for users to understand the data. Connect Cloud instantly connects to over 150 cloud applications, databases, and data warehouses, and provides fast connectivity to major data sources like Microsoft Power BI, Tableau, and Google Sheets. It also empowers users while centrally governing access, allowing teams to grant access to a diverse set of users while maintaining control over data access to all sources.

Our framework uses a combination of code generation on the front end to build native drivers for different driver/adapter technologies, allowing it to support multiple technologies consistently and easily add new ones in the future. The data access chain is a key component of this architecture, consisting of objects that implement core driver functionality through an interface called IDataAccess. This layer handles services such as opening and closing transport connections, metadata queries, query execution, and more. To simplify the implementation of OAuth protocol for authentication, we use an IDataAccess implementation that takes care of obtaining or refreshing OAuth tokens before commands get to the driver. The framework also includes a function and alias resolution component that transforms SQL query AST to make it simpler for the driver to interpret, and a client-side query engine that evaluates queries on providers with limited query capabilities. The goal is to push down as much computation as possible while providing flexible query capabilities to meet customer needs. Result sets are represented as objects implementing the IResultSet interface, which includes obtaining metadata about result set columns, iterating over results, and obtaining values from columns for the current row. Provider implementations can be created using a new, driver-specific IDataAccess implementation or by reusing an existing generic framework that hooks into an existing generic IDataAccess implementation. The Query Evaluation and Query Slicer components are present in all providers, either as provider-specific implementations or by reusing base implementations in our framework.

Capitalize has partnered with CData to simplify their customers' Workday analytics processes by providing industry-standard connectivity with Workday data, enabling clients to streamline interactions with Workday data and automate manual tasks, thereby improving the accuracy of business decisions.

The CData Driver architecture has several key components, including metadata caching services that transparently cache discovered metadata in memory or an external repository for performance advantages, and SQL normalization engines that simplify query interpretation by applying transformation rules to the Abstract Syntax Tree (AST) of a query. The drivers must support diverse query capabilities to work with business intelligence and analytics tools, which often generate complex queries automatically based on their internal rules. A generic OData implementation is also provided to simplify the implementation of additional drivers based on the standard, while other services such as connection pooling, bulk row management, row scanning, page providers, and parallel fetch support are implemented to reduce costs and improve performance. These components work together to simplify the development of a new driver, enabling developers to focus on provider-specific implementation details.

Modern enterprises rely heavily on data to remain competitive, but managing that data requires keeping pace with new information and evolving business requirements. As the tech stack grows, a modern data integration strategy is necessary to integrate data from disparate sources, including cloud and on-premises storage. The data connectivity and integration landscape has changed over the years, with organizations now using multiple applications and tools to analyze data stored in different places. To keep up with this trend, IT teams need to adopt best practices and technologies that enable real-time access to refined data, automating manual tasks and ensuring timely business decisions. By doing so, organizations can make the most of their enterprise data for advanced analytics and informed business decisions.

The choice between data integration and data virtualization depends on the organization's specific needs, including data volume, complexity, and integration frequency. Data integration is well-suited for long-term performance management and strategic planning, but may not be suitable for operational decision support applications that require intraday data updates. Data virtualization offers more flexibility and real-time access, making it a better option for applications requiring frequent updates and agile data management. Both methods can be used together to streamline data management processes and provide comprehensive insights to drive business initiatives forward. CData solutions support both approaches, offering flexibility based on specific requirements.