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7 Elements of a Data Strategy By Akshat Jasra

Akshat Jasra suggests that, without a robust Data Strategy for enterprise in place, execution is just next to impossible. Ckeck elements of effective data starategy now!!

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7 Elements of a Data Strategy By Akshat Jasra

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  1. 7 Elements of a Data Strategy By Akshat Jasra While most companies recognize that their data is a strategic asset, many are not taking full advantage of it to get ahead. In this blog, we discuss the elements of a data strategy that will help you make decisions based on data analysis rather than intuition. Let’s talk about how to get started with your own strategy. We’ve helped dozens of companies with varying levels of analytical maturity and technical needs craft their data strategy. Akshat Jasra states that, each of the following elements have been identified through this experience and can be applied to any organization looking to get ahead with their data. 1. Business Requirements Data must address specific business needs in order to achieve strategic goals and generate real value. The first step of defining the business requirements is to identify a champion, all stakeholders, and SMEs in the organization. The champion of the data strategy is the executive leader who will rally support for the investment. Stakeholders and other SMEs will represent specific departments or functions within the company. By starting with gathering and documenting the business requirements, we overcome the first roadblock to many IT or technical projects: knowledge of what the business is trying to accomplish.

  2. 2. Sourcing and Gathering Data Akshat Jasra states that, with a good understanding of what questions the business is asking, we can turn to the next element: analyzing data sources, how that data is gathered, and where the data exists. It’s unlikely that all data will be available within the organization and that it already exists in a place that’s accessible. So, we need to work backwards to find the source. 3. Technology Infrastructure Requirements Our first piece of advice is: Don’t get caught up in the hype and latest technologies; focus on the business reasons for your initiatives. Building a flexible and scalable data architecture is a complex topic for which there are many options and approaches, so here are some important things to consider: •To what extent can an operational system support analytics needs? Likely very little. It’s generally not best practice to rely on an operational system to meet analytical needs, which means a central data repository would be useful.

  3. •Is there a standard integration tool to get the data from source systems into the central repository? Will this layer of the architecture be leveraged for business logic so that the data is ready to be used? All of these considerations will go into an overall architecture. And, as with most designs, the more your requirements and future needs are taken into account, the more the solution will actually support the business. 4. Turning Data into Insights A data strategy should provide recommendations for how to apply analytics to extract business- critical insights, and data visualization is key. Many companies still rely on Excel, email, or a legacy BI tool that doesn’t allow interaction with the data. Often a tedious, manual process is required, and relying on IT to create reports creates a bottleneck. 5. People and Processes As we’ve stated, becoming data driven requires more than just technology. In this stage we look at the people in the organization and the processes related to creating, sharing, and governing data. A data strategy is likely going to introduce more data and data analysis and maybe new tools. 6. Data Governance Data governance is what ultimately allows enterprise level sharing of data and the oil that lubricates the machinery of an analytics practice. 7. The Roadmap The roadmap is the culmination of all the work we’ve done to this point and what makes all our previous work actionable. We’ve identified all that needs to happen to bring you from where you are to where you’d like to go, but before getting started with any design, build, training, or re-engineering of a business process, it’s critical to prioritize the activities. For each recommendation that will help bridge the gap from current state to the future state, define the feasibility and expected business value it will provide. As stated by Akshat Jasra, the plan should prioritize activities that are easiest to implement but also provide quick wins to the business. The roadmap should also contain a timeline that allows for celebration of incremental wins that are earned along the way.

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