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1. Make data accessible

Data today is like oil in the 19th century: People know the resource has tremendous value, but they’re still searching for the best way to extract it.

According to Tableau, a data management strategy is your company’s roadmap on how the organization will use data to achieve your objectives, goals, and targets. It guarantees that the collection, analysis, storage, collaboration, and just about any activity that has anything to do with data and its management, flows smoothly and effectively. An effective data management strategy enables companies to derive actionable insights from their data, while also streamlining data governance.

Insights, not merely the data these insights are based upon, are what is really valuable. If employees are empowered to answer their own analytical questions, then they don’t have to seek out data analysts for answers. That leads to faster decision-making while liberating data experts to focus on high-level projects.

2. Consider a cohesive platform that supports collaboration and analytics

You use search to answer questions about your data without having to consult a data analyst. Using ThoughtSpot’s relational search is simple, so anyone can use it. In the search bar, type what you are interested in exploring, for example revenue midwest sales rep  Searches return a set of results in the form of a table or a chart. ThoughtSpot likes to call this set of results in response to a search an answer. As you get better with ThoughtSpot’s search, you will be able to get more out of your data by performing more complex searches. There are a few basic things you should understand before starting a new ThoughtSpot search.

Using ThoughtSpot’s relational search is simple, so anyone can use it. In the search bar, type what you are interested in exploring, for example revenue midwest sales rep  Searches return a set of results in the form of a table or a chart. ThoughtSpot likes to call this set of results in response to a search an answer.

As you get better with ThoughtSpot’s search, you will be able to get more out of your data by performing more complex searches. There are a few basic things you should understand before starting a new ThoughtSpot search.

3. Provide tools to help the business work with data

 

  • Reusability takes from what has already been created for data management and analytics. For example, a source-to-target data pipeline workflow can be saved and embedded into an analytics workflow to create a predictive model.
  • Automation helps during model building and model management processes. Data preparation tools often use machine learning and natural language processing to understand semantics and accelerate data matching.
  • Explainability helps business users understand the output when, for example, they’ve built a predictive model using an automated tool. Tools that explain what they’ve done are ideal for a data-driven company.

4. How to Become a Data-First Company

To shift your company model to a data-driven one, follow these steps:

  • Employ data-focused roles at the top, such as a chief data officer (CDO) or chief analytics officer to oversee how data is being used in relation to overall business goals.
  • Develop a cohesive analytics strategy with defined end goals.
  • Collect only quality data that serves the overall analytics strategy.
  • Implement an easy to use digital analytics into employees’ existing workflows to encourage them to make day-to-day decisions based off data.
  • Create a rewards system that recognizes when employees and teams successfully use data to improve company processes, customer engagement, product and other innovations to drive growth

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