Common Challenges with Big Data Integration (and what you can do about it)
Did you ever think of what technical challenges you may encounter when planning your Hadoop implementation?
You should – 55% of big data projects fail1 and that’s not due to poor intentions.
It’s wise to consider why you are using Hadoop in your organization. Think about your use case. Can it be addressed by a traditional data warehouse? If not, are you injecting too much complexity into a simple- to-solve solution?
Remember, Hadoop is difficult to work with; this is a common challenge for users when asked. It requires expertise in many different programming languages. Frequently, critical time is wasted by organizations that have tight budgets but need this technology to reap financial benefits.
Another challenge involves big data itself. Companies are generating data in higher volumes and at a faster pace than ever before. What about the quality of that data? Do you know how good or bad it is? How are you going to improve it within the confines of your Hadoop ecosystem?
The good news is that if you plan wisely, you can navigate these challenges satisfactorily. A data management product that unites strategy and technology will serve you well.
Information Builders has one such product, iWay Big Data Integrator (iBDi). One of the great things about iBDI is that the interface is straightforward and easy to use. It allows users to ingest data from any kind of source and transform it as well, adding data quality to the mix.
Another great benefit allows you to use Sqoop, Flume, Kafka, and Spark without programming. Data warehousing employees can create data ingestion and publishing processes with no knowledge of the underlying technology. And once the data is transformed, and data quality is put into place, your data scientists can use this information in whatever analytics application you choose, for more concise results.
Whatever product you use to implement a big data integration, you would probably benefit from reading our new whitepaper, Real-World Strategies for Big Data. It not only covers challenges, but also discusses how strategize and succeed.
Feel free to let me know what you think, by commenting below. I look forward to hearing from you.