The goal of any business is to create a product or service that returns a decent profit compared to the expenses for creating, producing, distributing, and marketing something of value. While the innocent days of lemonade stands may have worked for us when we were 10 years old, to stay afloat in today’s fast-paced, data-driven consumer market requires bespoke information reporting. If you want to have the best opportunities laid at your feet to grow and develop your business, you need a system in place that successfully collects, analyzes, interprets, and issues reports based on the raw data.
That is where business intelligence and the Data Transformation Lifecycle come into play. These are the essential methods to inform your decision-making. By extracting data from various sources, including everything from how many visitors you get to a website to the time a customer spends on a support phone call, it allows you and your team to capture new insights that often result in higher profits.
What is Data Transformation
The data lineage of raw data is incredibly important to track because it is the lifeblood of modern business. Understanding where your data is being sourced and consumed then implementing tools that extract, record, and visualize this data is not only necessary, but also often the key to a competitive advantage.
Data Transformation takes this raw data and manipulates it into reliable information that can be used to increase the monetization of your business assets and processes. The goal is to place this raw data through a process that models metrics associated with your business KPIs (key performance indicators). This informs your team how close you are to attaining specific goals
How Data Extraction Gets to Business Intelligence Reports
The ability to leverage data visualization starts by first extracting data from key sources. This could include systems like social media, Salesforce, CRMs, and anything else that generates key metrics that can be stored. Essentially your organization is receiving data from databases or SaaS platforms and either extracting or replicating it into a data lake for reporting, analyzing, or machine learning purposes. This process requires cleaning, merging, and transformation before anyone in your company can effectively consider it consumable material that is ready for querying.
We have seen the call for businesses to step up the digital transformation process, which often includes AI/ML automation. These automation tools involve taking data from the disparate source systems and using it to lower operating costs, improve customer retention rates, increase production yields or improve sales effectiveness. or streamline your digital presence using common data analytical visualizations.
How to Visualize Data Transformation through Architecture
The structure we use to visualize this data being collected and cleaned is paramount to the overall reporting capabilities of any business. What works for a small website creation firm in the Pacific Northwest does not apply to a bank in New York City. Often, companies will leverage cloud data architecture to interpret data transformation results as a solution to crafting their own architecture. This could include concerns related to:
The point is to have data pipeline tools that improve workflow and send your information to either the human assets or analytical tools as quickly as possible. Gather up a response and implementation team comprising different members of your company from marketing to support staff, so everyone is involved in the final process and helps create cross-functional solutions.
- Data Sensitivity - a lot of so-called “big data” is from customer inputs or demographic sales information. This is often considered private and needs to be protected to avoid damaging leaks in the media or allowing competitors to leverage it against your business.
- Data Schema Management - how you organize your data concerning DBMS (database management) systems is crucial to interpretation. You want to make relative associations that all your company to make assertions based on logical inferences.
- Proliferation of Data – how to manage the vast amounts of data being collected, extracted, and analyzed impacts how you can report and interpret the data during visualization. You would not want to make an assumption for tomorrow’s sales figures using data from only a brief period 10 years ago.
- Data Sensitivity - a lot of so-called “big data” is from customer inputs or demographic sales information. This is often considered private and needs to be protected to avoid damaging leaks in the media or allowing competitors to leverage it against your business.
- Data Schema Management - how you organize your data concerning DBMS (database management) systems is crucial to interpretation. You want to make relative associations that all your company to make assertions based on logical inferences.
- Proliferation of Data – how to manage the vast amounts of data being collected, extracted, and analyzed impacts how you can report and interpret the data during visualization. You would not want to make an assumption for tomorrow’s sales figures using data from only a brief period 10 years ago.
- Recommendation Engines - implementing data filtering tools that utilize ML algorithms allows you to gain insights into areas of your business operations that may have never been considered before.
The Data Transformation Lifecycle
Luckily NextPhase Data Management Services makes this process of Data Pipelines and data visualization significantly easier by automating key aspects of the data transformation lifecycle. By sticking to key essential steps, we can present your collected information in a way that allows everyone on your team to make future decisions based on relevant, current, and historical data points.
1 – Data Discovery
We will access the various sources of your data from SaaS tools to analytical platforms and collect it through an ETL system into a data lake where it can continue through our processing.
2 – Catalog Your Data
Your raw data can now be cleaned through various agreed-upon policies that could include what kind of architecture you prefer to how to manage sensitive data that needs protecting. This is then placed into modeling form before moving to the next step.
3 – Move Data
Everything is either replicated or transferred to the data cloud. Our team can access it for further processing or your designated people for oversight and accuracy concerns.
4 – Transformation
This is the most exciting phase because we get to take your processed data and validate its authenticity, as well as curate for any possible outliers or integrity concerns.
5 – Automation & Visualization
Here you can leverage AI/ML automation to inform your decision-making or create custom reports that are given to leadership and anyone else in management requiring further insights.
This lifecycle is reliant on creating functions to ensure the overall structure and a reliable end product or report. This includes:
- Data Lineage - a map of the data journey from sourcing to final automation or reporting.
- Cloud Data Architecture – the rules and policies that govern how your data is collected, stored, and used.
- Data Infrastructure – guides and bodies that inform how to use collected data.
- Data Operations – how your data is supported through a range of services and processes.
- Visualization & Automation – how you want your data to be fed into AI/ML systems or reported on for decision making.
Leveraging Data Transformation for Your Business Operations
The more you can streamline and improve the data transformation system of your raw information, the better your potential decision making. This could be the single greatest competitive advantage you have to rise above the noise of your business niche or industry.
Working with our expert team at NextPhase Data Management services can help you better achieve your business goals and objectives. We have developed an automation library of pre-defined data transformation routines that can help expedite your data transformation journey.
Reach out to our expert support team today to schedule a consultation for our services. We look forward to walking you through our system or explaining how we can help enhance what you already have in place. Email us – hello@nextphase.ai .