What keeps C-suite executives and finance professionals awake at night? Is it the thought of new tax regulation, the next round of investor meetings — or something even more fundamental? Are the numbers right? Given the many recent high-profile examples of what happens when financial data isn’t accurate (for whatever reason), wondered how senior executives and finance professionals felt about the accuracy of their own data.
Siloed data sources, duplicate entries, data breach risk—how can you scale data quality for ingestion and transformation at big data volumes?
Data and analytics capabilities are firmly at the top of CEOs’ investment priorities. Whether you need to make the case for data quality to your c-level or you are responsible for implementing it, the Definitive Guide to Data Quality can help.
Read on the Definitive Guide to learn how to:
- Stop bad data before it enters your system
- Create systems and workflow to manage clean data ingestion and transformation at scale
- Make the case for the right data quality tools for business insight
Talend is a leading data integration and data management solution provider for data-driven companies. As an Advanced Technology Partner in the Amazon Web Services Partner Network, Talend provides fast development of Big Data, real-time analytics and ETL projects on Amazon Web Services, empowering companies to solve modern integration challenges by connecting business-critical data and applications from on-premises systems, cloud applications, web, social, and mobile apps in days at a predictable price.
In today’s hyper-connected digital world, access to data has become a top priority for organizations of all sizes. But as more businesses look to their own data to derive insights, they’re slowly realising that just collecting and analysing their own data can sometimes fail to generate game changing customer insights. To create true value, data insights need to be collected and compared against data sets from other organizations which provide unseen context and customer perspectives. And yet, this isn’t happening.
Unfortunately, many businesses haven’t yet developed the necessary framework to either collect or share this type of information. Internal processes restrict analysts from being able to do their jobs effectively, while a lack of vision stops businesses from seeing the opportunities inherent in connecting their data with that of other businesses. Ultimately, companies are either too slow to collect data themselves, or unable to partner with others.
Continue reading “Structure your business for Data Governance and Data Liquidity”