A data engineer is responsible for the ingestion, quality, integration, governance, and security of data – in short, taking data from various sources and making it reliable and useful. This enables data analysts and data scientists to use the data for business intelligence, data analytics, and building data products.

Many organizations lack the specialized data engineering expertise that is required to fully realize value from data. At Infostrux, we handle the data engineering for you. We build and manage automated data pipelines as a unified data cloud solution running on Snowflake.

For more information, please see our post The Dataland Zoo or download our white paper Go Further with Snowflake’s Data Cloud

Today’s data landscape requires significant domain knowledge to navigate. Businesses are striving to become increasingly data-driven, but investments are typically directed at the visible part of the iceberg — data analysis and data science, where value is realized through business intelligence practices. This often comes at the detriment of the data engineering posture of the organization, leading to a very robust business intelligence platform generating wrong insights from bad data with high confidence.

This is where we come in. We take on the many undifferentiated challenges of data engineering and deliver curated, refined data that your team can then use to generate significant, reliable value for your business at an accelerated pace.

Businesses face many common problems which can lead to BI, data analytics and data science projects to fail:

• Organizational silos produce data silos preventing value realization; we break them down
• Too much effort is spent on fixing integration failures before producing insights; we take them out of the equation
• BI projects fall into the “high confidence bad answers” trap due to unreliable data; we deliver certified data sets

Whether your data strategy is to drive growth, reduce costs, or mitigate risks, we can help. From medium-sized businesses with few data sources to large enterprises facing Big Data challenges, our team of data engineers can deliver data you can trust.

For more information, please see our Services page, or schedule a call with us today.

Our first step is to set up a discovery call. This is where we can learn more about your business’s specific needs, challenges, and goals. This also gives you the opportunity to ask any questions you may have and learn more about what we do.

Next, we need to dive further into the details of your domain to fully assess and diagnose your business requirements. During this stage, we will meet with your data team and review your technology stack.

Once we have gathered enough information from the call and our audit, we can put together a plan that’s right for you. We will deliver a detailed proposal, go over any questions you may have, and make any necessary revisions.

Upon approval, we will get to work. Depending on the package, you can expect our team to complete our services in as little as 4 – 6 weeks for a pilot (MVP) engagement, 2 – 4 months for a foundational engagement, and 4 – 6 months for a large-scale migration engagement.

We also offer ongoing monitoring, maintenance, and optimizations so as your business grows and evolves, we will be there to support you.

For more information, please see our Services page, or schedule a call with us today.

We offer the following services:

Data Engineering – Our teams build automated data pipelines to ingest data from a variety of structured, semi-structured and unstructured data sources, integrate the data into a unified data warehouse/data lake solution and engineer solutions for ongoing data validation, quality and governance.

Data Architecture – Our data architects work alongside our customers as consultants in analyzing, designing, prototyping and implementing data warehousing, data lake, and data analytics solutions on top of Snowflake’s Data Cloud Platform.

Data Analytics Implementation – We work with our customers to implement BI reporting and analytics solutions on top of Snowflake and provide assistance in developing reports and dashboards and optimize their performance and cost.

Data Science Support – Our teams build data lakes and implement appropriate technologies to enable access and provide compute capacity for our customers’ data science teams to perform data analysis, modelling and training of machine learning models.

Managed Data Cloud – We deliver automated data pipelines and validated data sets as a unified and managed solution offered as service, which includes ongoing monitoring, maintenance and optimizations.

For more information, please see our Services page, or schedule a call with us today.

Our pricing depends on a variety of factors, including number of data sources, the complexity of integration, and services required. To determine a price, we require an initial discovery call and a further audit to understand the specific needs of your business.

For a free 2-hour data analysis workshop, please see our Get Started page, or Contact Us to learn more.