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Using Timextender to Accelerate Predictive Analytics
Written by: Greg Horton, Head of Global Marketing, TimeXtender - September 5, 2019
A recent study indicated that the vast amount of companies surveyed are spending an excessive amount of time and resources trying to derive value from their AI but are delayed in doing so because of data-related challenges.
These data-related challenges could be poor data quality, the data needed for AI to examine is missing, or the data models created are flawed, among other factors. While organizations are spending time trying to align their data to help them achieve fully-functional AI, along the way, they’re left with a hollow toolset that doesn’t provide the AI insights they had hoped to achieve in the expected time frame. This contributes to the next major problem companies face.
The study also indicated that only one out of every three projects are completed on time.
These two drawbacks are obviously not good signs. But the good news is help is available. And that help is TimeXtender. With TimeXtender, businesses can significantly reduce the time to value derived from their data insights by substantially decreasing the amount of work required to build and maintain a corporate data estate. TimeXtender enables the consolidation, integration and centralization of all data into a single data repository for leveraging analytics and AI.
In addition, TimeXtender is compatible with most data systems, and its operational data exchange (ODX) supports hundreds of different file types, different databases, various work apps, and most any data source. All this translates into efficiency, speed and major time savings.
As we know, and discussed in an earlier blog post, even the most advanced AI platform cannot make sense of bad data. TimeXtender's automation engine makes data cleansing and modeling very simple to do. It cleanses, transforms, and models data into Azure with its easy-to-use, drag and drop interface. This enables users to supply quality data to AI platforms such as Databricks.
The bottom line is this: companies are looking for faster, more efficient and more economical ways to get to their data. By leveraging their data insights, businesses can then take advantage of predictive analytics to help them find solutions to questions and problems, and to attempt to forecast and plan for future market trends.
Using TimeXtender, businesses can easily build and maintain a data estate and reduce the time to insights by up to 10 times – accelerating their time to value for artificial intelligence, machine learning and ultimately predictive analytics.