We’ll help you ingest, integrate, and transform data for analytics with our world-class data design and programming services.
Data Engineering. Building the systems that power the insights.
Data engineering is the programming, design and management of data as it flows into and through an organization to become actionable analytics. Your analytic success is wholly dependent upon the efficiency and flexibility of your data engineering practices and platforms.
Choosing the right tool for the job is the first step. We recognize that not all data comes with simplified row-column access. The shape of data varies by volume, variety and velocity each requiring different technologies to get the job done.
We are masters of a wide variety of data engineering platforms including classic ETL and database programming tools, like Pentaho Data Integration, agile languages like Python and the growing Hadoop ecosystem including Spark, Pig, Hive and Map-Reduce.
More than just your average ETL Development
Traditional star schema databases are now only part of the story. Modern data architectures require designs that are optimized to the platforming technology. For example, many analytic databases including the growing SQL on Hadoop technologies perform better with flattened dimensional data instead of normalized star schema.
Additionally, when using Hadoop, data design extends beyond structure to format. If you’re planning on querying your data with Impala or SparkSQL, then you might consider formatting with Parquet. Smart design of your data takes into account its use and the available technology. We know how this works.
We think multidimensionally about multidimensional data.
Choosing platform, structure, format and programming language is essential to an optimal data design. Inquidia’s expert team will help you navigate the options and deliver scalable, extensible data engineering solutions.