Did anyone say big data would be easy? Consider what's involved. 1 Data must be ingested from all your existing systems. And then 2 transformed, tracked, merged, stored, and synchronized in a common data lke. And then 3 deployed as models and cubes for consumption by your reporting, analytics, and machine learning systems. That's all. 4 All you need to do is custom code you type management, change capture, incremental ingestion and transformation pipelines, track merging data lineages over time, design and optimize your models and cubes, scale a cluster, manage development to production migrations, govern a data catalog across a user base, and ensure all data is validated and available. No problem, right? I mean, there's a whole zoo full of tools, patterns, and techniques available these days, and brilliant technologists are able to work miracles with them. But there's an important question to ask here: 5 do you really want to hire, manage, and own your own software company?
Data engineering is 80% of the effort in enterprise data ops and orchestration, but maybe you would still say yes to this challenge. Tech monsters like Google and online gaming giants like Zynga certainly do. Those are where the automation processes driving Infoworks get their DNA. Or, 1 maybe you'd rather just have the agility of such automated, standardized, flexbile solutions available to meet your own recurring data engineering needs, 2 letting your staff launch new use cases 10 to 100 times faster, with 1/10th the resources, while retaining the flexibility to port to new cloud vendors and underlying technologies, as needed. 2 Maybe you'd prefer the simplicity of a code free, configuration focused approach to all your fundamental data engineering operations, 4 letting you expand the capabilities of a broader range of talent on your staff. 5 Maybe you'd appreciate the productivity gains realized by reducing the effort spent on forcing your high value talent 6 code variations of the same basic ingestion and transformation pipelines, over and over. 7 That's why we're here.
So, where does EDO2 fit into your infrastructure? 1 Modern enterprises companies have been working to overcome data siloes for decades, yet here we are. RDBMS, Enterprise Data Warehouse, Mainframe, Streaming, and other big buckets of data are scattered through different parts of your company. 2 Infoworks provides a single user experience for your Ops staff, Data Engineers, Data Scientists, and Business Analysts, to 3 ingest, transform, and optimize data from any source in your company into data models 4 in storage, 5 in memory, or 6 in pre-calculated cubes, as appropriate for your needs for speed, 7 all wrapped in operations, orchestration, and governance capabilities to keep your systems synchronized, and your data secure. This way 8 you can attach to a common, secure body of data from whichever reporting, analytics, AI and machine learning, or lower level technologies you may need. 9 With all of this flexibly and abstractly riding on your preferred Hadoop or Spark based big data infrastructure, and residing on premise or with your chosen cloud vendor.
Obviously there is a lot going on in this product, but in a nutshell we automate your 1 ingestion and synchronization of data from any number of sources into a common data lake. 2 We automate the process of combining and transforming this data as needed. 3 We automate optimizing and exposing this data in the manner best suited to your needs for access speed. 4 We automate the orchestration of when and how all these processes occur, to dance nicely with the ever changing service demands and capacities of your broader technical ecosystem. 5 We automate the installation, configuring, and scaling of your big data analytics, and more importantly, abstract it in a manner which lets you change cloud vendors and evolve underlying technology stacks, as your business needs demand. 6 We streamline and automate the auditing, cataloging, and secure governance of your data across user domains. 7 We automate the export of your transformed and optimized data into external systems, and 8 We maximize the availability of your data, by securely and durably ensuring access to verified copies.
So, what have you learned? 1 Yes, you can always roll your own. Libraries and points tools do exist to meet evolving data needs. 2 But not all enterprises want to run their own internal software factory. 3 Automated data engineering let you launch use cases more quickly, 4 expand the productivity of your staff, 5 reduce complexity, and 6 add a layer of abstraction easing the friction of inevitable future technical change. 7 Infoworks standardizes the ingestion, transformation, optimization, orchestration, operation, governance, export, and replication of your data, across and among all your many silos.
Infworks is like grease for your wheels. Come on back, and we'll keep showing you how it works.