Are you considering investing in your data?
So your company is investing in data analytics? Everyone is sooo excited, after all an investment in big data will give your company wonderful actionable insights that your teams will act upon immediately and unleash new initiatives. Profitable opportunities will start pouring in and revenues will go into overdrive…whoa not so fast! Sorry to sound like a wet blanket, an investment in your data is no doubt a sound idea, but considering how fast technology changes, will your data integration system will be relevant and functional in the future as well? You don’t want to spend millions of dollars on your data integration project only to have to overhaul it 2 years down the line?
Data integration issues that you may not have expected
In our experience, most companies are gung-ho when they implement their shiny new data integration platform. It works well for a while but slowly issues start creeping in- why are there so many bottlenecks? Data volumes just increased to 5x times and the new system just can’t cope. The company needs to add another data source but the integration tool is not compatible with it. What do you do then?
Think about future requirements, not just current needs
For starters, you shouldn’t be looking at data functionalities in the context of your current requirements but also consider how you can make your data implementation pay off with great ROI in the future as well. One thing to look for any data integration system is its scalability. Big data is growing exponentially – from a meagre 10 zettabytes in 2015 to a whopping 180 zettabytes by 2025, as predicted by IDC. Imagine if your data grew 10x in the next 2 years, could the system handle it? What if you needed to use your data for Machine Learning – could you do so without hiccups (and extra expenditure)? What if you needed to change your data integration tools, how would that work out, would it blow another huge hole in your data budget? Not to forget your legacy data of yesteryear, would that data forever be siloed or could it be extracted to join the party?
If you would like to know more about keeping your data integration systems effective, usable and scalable in the future, download our ebook: 9 ways to future-proof your data.
Everything begins in the Cloud
Make sure your data integration journey begins with the Cloud. Integrating data in the Cloud offers unprecedented scalability and agility. According to Cisco, moving to the cloud can improve a business’s agility (by 29%) and reduce payback times by 30%. With Cloud data integration you can also save on hardware costs that add up considerably over time. You also need to ensure your data integration software has been created for the Cloud and can ingest data from multiple sources in real-time without impacting source systems.
Get the data integration software that enables you to do more.
Using the right data integration software is paramount. Did you know 99.5% of collected data never gets used or analysed (Cisco)? And less than 50% of the structured data collected from IoT is used in decision making (Wikibon)? The right data integration tools will help you get the most out of your data, so you can access it very fast and use it easily. Data integration tools should preferably be automated, codeless and self-service. They should be able to ingest multi-source data, replicate all changes continually with log-based CDC and merge, transform and prepare data for Analytics and Machine Learning in real-time.
Get the BryteFlow Free Trial
BryteFlow is one of those rare data integration software that can happily stand upto changing technologies in the future. It continuously replicates data from any database, any file and any API in real-time to Amazon S3, Amazon Redshift and Snowflake. It can blend and prepare any data for Machine Learning and Analytics. Get a free trial with complete extended support with screen sharing and consultation.