“ Data is the new oil ”.
British mathematician Clive Humby compared data to oil to illuminate its significance. He used this metaphor to indicate that data is immensely valuable, but if unrefined it is useless and ineffective: only once it’s refined and analyzed, does it create extraordinary value. In essence, data is of little value to companies if it is not refined or cleansed.
Data has undergone massive, exponential growth in the past few years. This data explosion has impacted organizations’ ability to refine, process data, and extract insights for driving their businesses forward. In doing so, they need to collect, organize, and analyze their data across the multi-cloud, hybrid cloud, and data lakes that make the job overwhelmingly complex. The task of handling big data becomes even more arduous if traditional ETL tools are used. This is because legacy ETL tools support only a limited number of delivery styles and involve extensive hand-coding. Ergo, companies are unable to unlock true value from their data. Not to mention, delays and discrepancies in data can impact decision-making.
So, organizations must leverage a modern data integration solution that synchronizes and prepares data to make it fit for use. These solutions allow enterprises use and analyze data to streamline their business journey by:
Facilitating Large File Data Ingestion: Modern data integration platforms offer large file data ingestion capability to harness 5GB to 100 GB of data without the need for any specialized custom code or hardware appliances. Plus, they can easily access data from multiple sources using pre-built, pluggable connectors. In short, these data integration solutions process multi-GB files, ingest and transform large volume of data, and deliver data from different sources in a common format timely and reliably.
Ensuring Data Quality: Data must be accurate, complete and relevant. Bad data leads to bad analysis, which causes teams to make bad decisions. Modern data integration solutions enable analysts detect quality issues in data. Analysts can automatically import, profile, and assign a quality score to customer data. They can easily create logical automation rules using a graphical interface to look for certain abnormalities in the data. Moreover, the encrypted environment offered by these tools stops unauthorized access of all kind.
Streamlining Data Transformation with AI: Data transformation is important as this step helps organizations organize and transform data to make it fit for analysis. Delays and errors in this process can disturb decision-making and hamper business growth. Modern data integration platforms harbor AI-powered data mapping technology to allow organizations accelerate data transformation with accuracy. By making data transformation faster and precise, companies can make informed decisions and become easier to do business with.
Simply put, organizations can deploy modern data integration platforms to analyze, process, and transform huge volumes of data faster for improved decision-making and accelerated growth. To dive deeper, contact our integration experts and learn why Adeptia’s data integration solution is the best fit.