Your enterprise is facing a data management crisis. How can you solve it?

I understand the challenges that come with data management. To solve this crisis, we can implement a comprehensive data governance strategy. This includes establishing clear policies and procedures for data collection, storage, and access. We can also invest in robust data management tools and technologies, such as data analytics and cloud storage. Additionally, regular data audits and employee training will ensure data integrity and security. By taking these measures, we can effectively manage and leverage our data for business growth and success.

In addressing your enterprise's data management crisis, first assess your data situation by evaluating data volume, diversity, and velocity. Identify gaps in data storage, security, and accessibility. Implement a robust data governance framework, ensuring compliance with relevant regulations. Invest in scalable, efficient data storage solutions like cloud services. Prioritize data quality, accuracy, and consistency through regular audits. Train staff in data literacy and management best practices. Finally, consider adopting advanced analytics and AI tools to optimize data utilization, driving informed decision-making and strategic planning.

In a data crisis, swiftly pinpoint the root and extent of the issue. Gather comprehensive details about the impact on your data. Key to navigating the storm is transparent communication with stakeholders, providing clear updates on the problem's status and anticipated resolution. Effective crisis management hinges on rapid, informed decision-making. ??

During the crisis, the quick assessment of the situation is necessary. Data Management professionals need to view the situation in 2 perspectives. One is technical perspective and another one from business perspective. The evaluation of the scenario from multiple perspectives help understand it efficiently and plan for resolving it.

Na minha vis?o, entender qual é o cenário atual e quais s?o os pontos mais críticos dele s?o passos cruciais para defini??o das prioridades e de onde de fato os maiores esfor?os precisam ser empregados e de que maneira. Depois disso, estruturar um roadmap com planos de a??o, dando clareza das interdependência entre áreas, quem s?o os responsáveis/pontos focais de cada tema, qual valor financeiro necessário, s?o fundamentais para fluidez do plano e normaliza??o do cenário.

?? Set Data Goals & Metrics, Ensure your data management aligns with business objectives by establishing clear data goals and metrics. Aim for high data quality, availability, usability, and security. Implementing specific indicators cultivates a data-driven culture, sharpening focus and coordination in your data management efforts.

Data management can be applied with an understanding of current data and a variety of data then make a strategic plan to apply data governance and validation rules for new data onboarding into the system. Adopt AI tools to analyze the data problems and apply solutions and last but not least train your staff with data handling and training in new technologies to handle data in an advanced way.

Define and agree a set of data principles with your key stakeholders. This should include things such as: - ownership - retention - publication - security - documentation

There are so many areas to cover in this step, Cyber , accuracy, quality , accessibility , retention , compliance and the list goes on and on. Alluding and agreeing with @Mukundan A P and @Tim Riley what I have found to be an extremely valuable tool in introducing / maturing and maintaining a Data Driven Culture beyond the Continuous Education and mandatory compliance and regulatory training exposure most of our companies are mandated to provide had been one to no more than 4 key qualitative metrics related to your data issue/crisis in your JD's ( Job Descriptions ), in your vendor / partner MSA's ( Master Service Agreements ) and so on. Literally start at the start and be unapologetic about it, if you want to work for / with us data is ...

Antes de pensar em como resolver a crise, a organiza??o deve realizar um inventário para entender quais dados s?o tratados, onde est?o localizados, quais processos de negócio utilizam quais dados e, quais opera??es s?o realizadas por quais usuários / áreas. Com base no resultado deste inventário, a organiza??o poderá especificar e priorizar as a??es necessárias para superar a crise no gerenciamento de seus dados.

??? Choose Tools & Platforms Wisely, Opt for the right data tools and platforms tailored to your needs. From data integration and quality tools to analytics and storage solutions, the proper selection simplifies processes, expands capabilities, and enhances productivity.

Recognise that different types of data may need different tools and platforms to process them. Data may be structured, semi-structured or unstructured and in a wide variety of formats. Refer back to your data goals and ensure that any products you choose will help you meet these goals.

Most likely you already have tools, technology and processes otherwise you would not have any data. Examine what you already have in-house. Will these help you in resolving your data management issues? Start here so you don't start introducing more debt and complexity at the expense of the Company. If you require further tooling be exact in your assessment of your needs. Put together an iterative approach for improvement. Only tackle what you can and should afford (based on cash on hand and current skillsets). Remember any net new tooling comes with a long tail for resourcing and costs. And stay away from big sales. The worst you can do is trust someone on needing a big solution and big tools. Most likely you don't.

?? Implement a Robust Data Strategy, Adopt a comprehensive data management cycle: collect, prepare, analyze, share, safeguard, and review your data. This systematic approach ensures consistency and efficacy across all data-related operations.

Only start your data management plan if you successfully profiled and catalogued all of your data first, selected proper tooling and established an iterative and successful implementation plan. Be practical and break the program into manageable chunks. It probably took you a while to get into the situation that you're in so don't expect to fix it all right away. The data debt should start to resolve as you start to tackle the priority issues. Determine if the issue is within the generation (source system/business application), definition (metadata), transformation (ETL), staring (EDL, EDW, DM), or dissemination (Reporting/Analytics). Again be practical and approach appropriately.

Conduct a data mapping and indexing exercise, which codifies responsibilities, usage as well storage, and points of sharing and transfer.

?? Monitor & Refine, Regularly track and evaluate your data management using specific metrics. Seek feedback from users to pinpoint and address any shortcomings. Continuous refinement is key to maintaining and elevating data quality and utility.

In my experience, it’s pivotal to consider implementing robust data governance practices within the enterprise, investing in advanced data management tools, and fostering a culture of data responsibility among employees.

Don't put yourself right back to where you started prior to fixing your data management problems. There will always be new and exciting issues to tackle if you're a viable and growing business. You will generate new data. You will acquire new data. There will be new technologies and processes that will need to be monitored so that they are in alignment with your new strategy. Be diligent and keep true to your measurements around your data management health and data debt. Keep an eye on your metrics of data health and constantly improve.

Monitoring data stores for abnormal trends is the most critical thing you can do to alert you to problems before they become crises. When designing data management solutions, always allow sufficient time and resources for data trend monitoring, failure alerting, dashboards, etc.

Based on what I've seen, when data leaders lose sight of the big picture, it's helpful to bring in an outside perspective from someone who can approach the problem without emotional attachment. Hiring a high quality data management specialist advisory firm can help you reset and push forward to data nirvana!

Amidst a data crisis in an enterprise, a visionary leader scripted a narrative of resolution. The crisis, a looming tempest, demanded strategic orchestration. * A rapid assessment, the unsung hero, emerged as the compass, diagnosing the root causes swiftly. * Cross-functional collaboration became the storyteller's stage, aligning diverse teams for a unified solution. * Agile frameworks stood as vigilant guides, adapting strategies to navigate the evolving crisis. This narrative unfolded as a strategic composition, where rapid assessment, cross-functional collaboration, and agile methodologies converged, orchestrating a resolution that transformed crisis into an opportunity for improved data management within the enterprise.

When there is a data management crisis, a quick evaluation of the scenario needs to be done. The solution for the crisis situation needs to be thought in 2 angles: Immediate and long term. Immediate or short term (aka: tactical) solutions are quick things that can be done in order to run the important things for the business. Long term solutions are strategic plan to make the things stand up to support the business, including the plan to prevent any future crisis.

Hire a brilliant data management consulting firm like Ortecha! Sorry, couldn’t resist that. Seriously, you need to get the right expertise involved. You need people who have solved data management issues before and leverage their knowledge and expertise.

Incorporate data management and protection in disaster risk management and business continuity strategies.Conduct data impact assessments periodically.