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Modern data integration tools and data engineering techniques can simplify and speed up the process of cleaning, transforming, and bringing together data from all of your sources to make it analytics-ready.
Cloud-based data architectures provide the ability to ingest new data sources in minutes and scale your storage and compute just as quickly. This flexibility increases the potential to get more value from your data—but for many organizations, the rapid accumulation of data has resulted in messy, siloed data, leaving them wondering how to make sense of it all.
By combining our data engineering skills and our deep expertise with the modern data stack, we will make sure your data pipeline efficiently gets your data from all its sources to a state where game-changing analysis can happen.
We develop, manage, prepare, transform, and deliver data flows to enable analytics at scale.
We will help you select the right data integration tools and techniques for your disparate data and determine where you should integrate your data, such as in a data lake, a persistent staging layer in a data warehouse, or a dimensional warehouse. We will also prioritize which data to integrate—and which to not—to control your costs associated with integrating, transforming, and storing your data.
We design and implement data pipelines that utilize modern tools to automate workflows and testing, standardize and speed up data transformation, remove data engineering bottlenecks, and bring more people in different data roles to the pipeline development process so that your data is ultimately more useful for decision making.
Your data needs to be cleansed, combined with disparate data, and enhanced with derived business logic to create a trusted business-ready layer in your data warehouse. We help you transform raw data into actionable information using tried-and-true principles, technologies, and techniques to create robust analytics solutions for end user consumption.
We’ve created reusable frameworks for ELT and ETL paradigms which allow you to quickly ingest data to your data warehouse with consistent naming conventions, auditable processes, and easily understood lineage for the ingestion pipeline.
We will help you establish realistic standards and thresholds for data quality, determine your best approach to data cleansing (sometimes human intervention makes more sense than expensive technology), optimize your existing cleansing tools, and get buy-in from your organization to support initiatives that promote data quality.
Our data engineers were able to replace their individual Swiss army knives of data scripts, spreadsheets, and pivot tables with a standardized data transformation process—and what would have taken months now takes weeks or days.
It can be overwhelming to keep up with all the data engineering software and data integration tools flooding the market.
Our consultants will help you choose the right tools in the context of your overall data architecture and enable your data teams to develop their data flows more efficiently and get trusted data to the business, faster.
Guided by proven data engineering practices and executed via modern technologies, we help organizations become more efficient with the data transformation process so they can spend more time analyzing.
The data models developed by Analytics8 in our Snowflake environment now automate the data ingestion process and allow us to scale the solution to various clients, saving us time, money and improving our customer satisfaction.
Sign up to meet with one of our analytics experts who will review your data struggles and help map out steps to achieve data-driven decision making.