Analytics

BigQuery Studio lets analytics practitioners use SQL, Python, Spark or natural language directly within BigQuery, to streamline analytics workflows.

By integrating Vertex AI foundation models in BigQuery, you can analyze unstructured data from right inside BigQuery.

Advanced marketing analytics help you simplify multitouch attribution, create tailored marketing campaigns, and maximize return on investment (ROI) across channels. It helps you seek patterns and insights to improve marketing performance. These days, you can’t do online marketing without advanced analytics. Moreover, you need the right tools and skills to make sense of data scattered across multiple apps.

Ever had your live app crash after a new update, forcing you to spend your weekends fixing it? Let us guess, an enthusiastic developer introduced a change without testing it thoroughly. But it’s not just app development that can go rogue. Whether it's last-minute changes to client reports, tweaks to your marketing campaign, or any other update in a live setting, unexpected problems can crop up.

Data warehouses and data lakes represent two of the leading solutions for enterprise data management in 2023. While data warehouses and data lakes may share some overlapping features and use cases, there are fundamental differences in the data management philosophies, design characteristics, and ideal use conditions for each of these technologies.

Kafka Connect is an open source data integration tool that simplifies the process of streaming data between Apache Kafka® and other systems. Kafka Connect has two types of connectors: source connectors and sink connectors. Source connectors allow you to read data from various sources and write it to Kafka topics. Sink connectors send data from the topics to another endpoint.

In the digital age, data is the lifeblood of any organization. The way you store and analyze your data can significantly impact your success. This is where data warehouses come into the picture. Data warehouses are essential for businesses of all sizes, as they provide a central repository for data from a variety of sources, which can then be used for analysis and reporting. This data can be used to make better business decisions, improve operational efficiency, and identify new opportunities.

I’m calling it now. The next battleground for analytics adoption among business users will be the productivity suite. Let’s unpack that statement by considering these two examples: Traditional BI has always forced you down a one-way street for answers—drop what you are doing, login to the BI tool, and pray to the data deities that you can find the answer you’re looking for.

Data integration and migration can be quite overwhelming and complex. It's easy to underestimate the complexities of managing data between different sources and destinations. However, diving into it without thorough planning and the right ETL (Extract, Transform, Load) setup could impact your business goals and deadlines, or even exceed your budget.