DataBuck
Big Data Quality must always be verified to ensure that data is safe, accurate, and complete. Data is moved through multiple IT platforms or stored in Data Lakes. The Big Data Challenge: Data often loses its trustworthiness because of (i) Undiscovered errors in incoming data (iii). Multiple data sources that get out-of-synchrony over time (iii). Structural changes to data in downstream processes not expected downstream and (iv) multiple IT platforms (Hadoop DW, Cloud). Unexpected errors can occur when data moves between systems, such as from a Data Warehouse to a Hadoop environment, NoSQL database, or the Cloud. Data can change unexpectedly due to poor processes, ad-hoc data policies, poor data storage and control, and lack of control over certain data sources (e.g., external providers). DataBuck is an autonomous, self-learning, Big Data Quality validation tool and Data Matching tool.
Learn more
Google Cloud BigQuery
BigQuery is a serverless, multicloud data warehouse that makes working with all types of data effortless, allowing you to focus on extracting valuable business insights quickly. As a central component of Google’s data cloud, it streamlines data integration, enables cost-effective and secure scaling of analytics, and offers built-in business intelligence for sharing detailed data insights. With a simple SQL interface, it also supports training and deploying machine learning models, helping to foster data-driven decision-making across your organization. Its robust performance ensures that businesses can handle increasing data volumes with minimal effort, scaling to meet the needs of growing enterprises.
Gemini within BigQuery brings AI-powered tools that enhance collaboration and productivity, such as code recommendations, visual data preparation, and intelligent suggestions aimed at improving efficiency and lowering costs. The platform offers an all-in-one environment with SQL, a notebook, and a natural language-based canvas interface, catering to data professionals of all skill levels. This cohesive workspace simplifies the entire analytics journey, enabling teams to work faster and more efficiently.
Learn more
IBM Cognos Analytics
Cognos Analytics with Watson brings BI to a new level with AI capabilities that provide a complete, trustworthy, and complete picture of your company. They can forecast the future, predict outcomes, and explain why they might happen. Built-in AI can be used to speed up and improve the blending of data or find the best tables for your model. AI can help you uncover hidden trends and drivers and provide insights in real-time. You can create powerful visualizations and tell the story of your data. You can also share insights via email or Slack. Combine advanced analytics with data science to unlock new opportunities. Self-service analytics that is governed and secures data from misuse adapts to your needs. You can deploy it wherever you need it - on premises, on the cloud, on IBM Cloud Pak®, for Data or as a hybrid option.
Learn more
DaLMation
Enable your data team to concentrate on what truly matters. Instantly provide answers to on-the-spot inquiries from business stakeholders. Stakeholders receive immediate responses to their questions. Non-technical users can directly pose questions in Slack or Teams, and the Data Analyst Language Model (DaLM) delivers the answers swiftly. This approach minimizes the time wasted on ad-hoc inquiries, allowing for a sharper focus on analyses that contribute to revenue enhancement. By empowering analysts to prioritize critical tasks, you enhance overall productivity. Simply access a file containing previous queries to kick things off. DaLM assimilates the business logic inherent in these queries and continually refines its performance as analysts engage more with the Integrated Development Environment (IDE). Initiate the process in just five minutes, regardless of your database's size or complexity. We ensure that no data is tracked, and your database's actual content remains within your environment. While the schema and query code are shared with the model, no real data is transmitted, and any personally identifiable information (PII) within the query code is adequately masked. This guarantees not only efficiency but also the utmost security and privacy for your data.
Learn more