Too many organizations start their data projects at the wrong end of the pipeline. Although challenges with data quality, integrity, access, and visibility are all important issues to address, a project should never start with the data. The reality is that all investments in data are meaningless if no business value can be gained. And this requires starting at the other end of the spectrum - evaluating the business problem to identify how data can help drive change within the organization.

There is no question about the usefulness of big data these days. However, if you want the best data, you need it to be as accurate as possible. That means that your data has to be up-to-date, correct, and clean. Using one of these top data cleansing tools can help you be sure of this.

Demand for both entry-level and highly skilled tech talent is at an all-time high, and companies across industries and geographies are struggling to find qualified employees. And, with 1.1 billion jobs liable to be radically transformed by technology in the next decade, a “reskilling revolution” is reaching a critical mass.

The AlloyDB connector from Integrate.io empowers organizations to rapidly consolidate all of their data into AlloyDB—a high-powered, Google Cloud database that is 100% compatible with open-source PostgreSQL. By serving as an easy-to-set-up, high-speed data pipeline to AlloyDB, Integrate.io helps businesses modernize their legacy proprietary databases by migrating them to open-source, PostgreSQL-compatible systems.

Today, we’re hearing from telematics solutions company Geotab about how Google BigQuery enables them to democratize data across their entire organization and reduce the complexity of their data pipelines.

Analytics and data visualizations have the power to elevate a software product, making it a powerful tool that helps each user fulfill their mission more effectively. To stand apart from the competition, today’s software applications need to deliver a lot more than just transaction processing. They must also provide insights that help drive better decisions, alert users to matters that require their attention, and deliver up-to-the-minute information about the things that matter most.

Organizations are improving the quality of their marketing analytics at less cost, which is translating into more overall marketing efficiency – all by adopting the modern data stack.

In the past, most software applications were all about “data processing.” In the parlance of old-school management information systems, that meant an almost exclusive focus on keeping accurate transactional records alongside any master data necessary to complete that mission. Transaction processing is important, of course, but in today’s world, applications are expected to deliver a lot more than that.