Handle new class of data problems

In the last couple of years, we have seen data analytics move from being just a fad to a key to growth. It has impacted the business a lot more that we had previously imagined.

Information is now coming from every nook and corner of the organization, which is truly useful for driving decisions. With the newer distributed storage and processing technologies, organizations are able to store and query raw data there by enabling them to perform faster analysis. They are now able to get down to every single transaction out there and build correlations.

Role of Analyst

With this increased demand from business users, data analyst are now expected to curate more and more data from these variety of sources; perform cleaning and enrichment to bring the data into a format that will allow analytical tools to process it.

Analysts are required to build ETL workflows or SQL scripts which typically take months to implement. Moreover, the ETL process is not agile enough for analyst to handle changes in data and adding newer data sets. For smaller data sets, they take a rather painful option of cleaning it in excel sheets with complex formula and without any data lineage to recover from failures or errors.

Unfortunately, most of the businesses are still taking a reactive approach to data cleaning. With data aggregation and preparation taking about 80% of an analyst’s time, we need a more productive approach to transform raw data to actionable data. Additionally, business users should have the ability to work with disparate data sources and perform iterative data cleaning tasks and offload this trivia tasks from IT.

Ideata Analytics Approach

At Ideata Analytics, we are able to solve this problem with a truly redefined approach to handle data management challenges. With a variety of supported modern big data sources and traditional databases and flat files, users can now quickly get access to the data they need; use the suggestive visual data preparation to perform faster data integration, transformation and cleaning; and use a simple drag and drop interface to do ad hoc analysis.

With simplified and shortened load-combine-clean-analyze cycles, users can gain deeper insights into their business and reach to decisions faster. Register for a demo with us to learn more about how we can solve your data problems.