Are you planning to transform your data into business decisions? Or start the data gathering process you always wanted to? Since there’s one thing that you cannot miss — identifying the pain points you want to gain insights on.
Based on your company’s strategy, goals, and target customers, you should prepare a questionnaire. This will walk you through the data breakdown and help you draw business insights through the proper data discovery process.
You might be wondering what is data discovery?
Data discovery is the collection and evaluation of data from various sources and is often analyzed to understand trends and patterns in the data.
You may ask why Data Discovery? Well, the answer is simple. Your data won’t communicate unless you ask the right and relevant questions!
And how will you know what’s the ‘right’ question to ask? Read on, to know more.
It is essential to gain context and clarity from the audience and end-users. You need to understand their key challenges, activities, and goals.
Three dimensions can help you keep track of your data and give your questions a sharper focus:
- It starts with identifying the problems, fundamental challenges, or issues your audience wants to solve.
- Once the problems are identified, you then determine the measures, key metrics, and other data points used to highlight the problem and monitor the performance of the initiatives.
- Further, you need to plan the outcomes. Set a strategic goal or the desired result your audience wants to achieve. The key activities and strategic initiatives your audience has implemented to achieve an outcome will be the last step of the process of analyzing the data and reporting conclusions.
Rawcubes is a pioneer in providing a completely managed end-to-end data management software that enables you with data discovery tools, data intelligence, and integration. DataBlaze’s Knowledge Explorer engine can help businesses profile and discover data about their customers. It enables an optimized process for instantaneously searching customer surveys, feedback forms, sentiment analysis, and other fundamental data points, all in real-time using natural language processing.
With NLP algorithms, the Knowledge Explorer can extract key business conditions from your dataset to maintain a glossary of these conditions with their relationships. The collection of business terms and relationships can help you ask better questions from your data.
DataBlaze, with its NLP capabilities and Knowledge Explorer, can help you build business terms and their relationships. This, in turn, can help you get a better context of the business use case and consequently ask relevant questions from your data.
Below are four steps that will help you to ask the right questions from your data.
In order to ask meaningful questions about your data, you and your team should be adequately aware of your data and its business relationships. Familiarity with discovered data sources, defined terms, and their relationship, makes onboarding new data consumers relatively a more simple and more effective process.
No data engineer works in a silo nor should they work on data isolated into silos. You should understand the projects and goals of different teams and try to consolidate all the silos into a single repository of data. This enhances productivity and quality.
Establishing OKRs and KPIs can help you find gaps in the business. Identifying the gaps can further facilitate a roadmap for relevant decision-making with an alignment toward your business goals. With augmented data discovery and our Knowledge Explorer, you can get answers to specific questions based on the terms/ metrics and their corresponding relationship with the business KPIs
Spending time aimlessly to determine something that eventually turns out to be non-essential can decrease your team’s productivity. It might also not weigh much in the actual decision-making process. With well-defined terms and their relationship, it gives you a jump start to ask the relevant question(s).
Let’s understand this with an example of a multinational organization that has incorporated DataBlaze into its data architecture. The client’s data sits on an ITSM application that manages the company’s customer support function.
Now there can be instances when the marketing team wants to see some numbers. How do you achieve that? Studying the brand impact based on holistic information from that third-party system and its digital assets is crucial to making business decisions.
We addressed the concerns, which include but are not limited to –
1) The impact of the average resolution time on the net promoter score,
2) Customer support survey feedback’s impact on brand loyalty,
3) The Impact of cycle time on the customer’s experience
Do you also want to know the questions that you should ask your data to make the right decision?
DataBlaze can assist!
Our data discovery solution enables you to query, integrate, and manage data from disparate sources. DataBlaze helps you gain visibility into your enterprise data with its robust NLP capabilities.
Empower yourself with a unique self-sustainable data management platform. Gain access to customizable data strategy templates, build Intelligence on your data, and blend data into datasets for analytics. Our augmented data discovery feature extracts, combines, and transforms your data capabilities to provide relevant insights when needed.
With our Knowledge Graph propelled by ML models, you can automatically build business terms and their relationships which will ease your data discovery process. This serves a two-fold benefit. Firstly, it reduces the time it takes for your data professionals to give you decision-driving information. Secondly, it lets you identify the questions that you need to ask in the first place.
Get comprehensive insights into your data and ask the right questions with DataBlaze.