Our Data Strategy Consultancy Services to Deliver Your Data Analytics Solutions
PTR have been assisting clients with their data strategy solutions and data analytics solutions for over 30 years and we have certainly seen a few changes over that time! One thing that hasn't changed is the value of business data and the wealth of information hiding behind it that can offer valuable insight and drive business decisions.
With the sheer volume of data now collected and stored, and the distributed nature of application solutions, resulting in data located across on-premise, service and cloud-based repositories with varying data structure and architecture, the challenge of integrating all that data and delivering a single source of truth for data analytics is a huge challenge.
We are familiar with most of the challenges you have faced and will face at one time or another and we're well placed to use our wealth of experience to help you build your Data Strategy and define a Data Analytics and Business Intelligence roadmap to reach your goal of a "One Truth" reliable, trustworthy 360-degree view of your business data.
The following diagram highlights the key layers of a Microsoft Azure based BI solution and gives inisght into the many considerations behind a BI Data Strategy.
Data Strategy - Reliable Insight Depends on Reliable Data
Any Business Intelligence Solution starts with a strong Data Strategy.
A well-defined Data Strategy will help you identify the valuable asset of information that you have distributed around your organisation's numerous business applications and how you might use it to provide valuable insights not just into what has happened historically, but why it happened, and how you can use this new knowledge to minimise risk and exploit new opportunities that drive future business decisions.
What Is Data Strategy?
In summary there are four key areas to be addressed in your Data Strategy:
- Data Governance
- Data Management
- Data Architecture
- Business Intelligence
Developing a Data Strategy to drive a successful enterprise wide Business Intelligence solution requires a great deal of research, information gathering, forward thinking, stakeholder collaboration and analysis across your organisation to ensure that a future proof, fit for purpose, affordable, performant and stake holder engaging data analytics solution is achievable.
A successful Data Strategy requires the involvement of key business stake holders and data stewards who drive data governance and effectively "own" the data. It also requires the involvement of data strategy experts who have a wealth of experience in different types of data, different enterprise business applications, the challenges presented by big data, legacy, current and emerging technologies and architectures. It also requires the expertise of those who can understand the current and future data analytics requirements across the business.
If you are new to data strategy you may need a bit more of an explanation of what these four key areas refer to.
Data Governance
Data Governance is about the availability and use of your data, and about the integrity and security of your data. The management of these areas may be governed by a mix of internal and external policies and agreements. At all times you must ensure that your data is secure, consistent across the whole enterprise, reliable and trustworthy. Without data governance you run the risk of inconsistent and inaccurate reporting, which may lead to conflict and disagreement between different business functions, but also to poor business decisions driven by inaccurate information.
As organisations rely more and more on Data Analytics platforms to deliver insights and drive business decisions data governance becomes increasingly more important. Poor data governance can also lead to severe security breaches as data moves from one environment to another without ensuring consistent security and integrity rules are implemented across all platforms.
Data Management
Data Management is about integrating and storing data. Data is gathered from many enterprise systems and when integrated it will require cleansing, preparing, validating and ensuring data quality in readiness for data analytics.
Data Architecture
Data Architecture can fall into three categories:
- Conceptual
- Logical
- Physical
In simple terms conceptual architecture is where we look at the overall picture at a high enterprise level identifying the key business elements and information assets and would involve the data owners across different sections of the business - those that responsible for the generation and use of the data.
The logical architecture is where we define the relationships between business entities. A logical architecture would be developed by solution architects and designers.
The physical architecture is the actual physical software implementation, the data platform. The physical data solution defining the underlying storage and service architecture such as cloud or on-premise data platforms, data lakes, data warehouses, business models.
Business Intelligence
Business Intelligence is where the magic of turning your datasets into insights takes place. Your data Strategy should define your current and future requirements in terms of key business drivers. The Business Intelligence aspect of your data strategy is where you can turn your wealth of data into a valuable business asset delivering data analytics solutions consisting of insightful and engaging dashboards and artificial intelligence driven analytics operations to improve business decision making and drive business processes.
Defining a Data Strategy - What have you got and where are you going?
Data Strategy is not a one type fits all and every organisation faces different sets of challenges which must be idenitifed, considered and overcome. PTR specialise in offering independent, technology agnostic strategic advice and consultancy on the whole data platform, particularly with a view to supporting a successful Business Intelligence platform. Our Data Strategy consultancy services can help you towards a robust and future proof data strategy.
This may include for instance:
- Audit and review of existing Data Estate
- Assessing the suitability of a Data Warehouse and subsequent design and implementation
- Requirements for separate enterprise grade modelling platform
- Suitability of public cloud offerings
- Challenging existing data collection procedures
- Opportunities for further Data Consumers
- Data Driven workflow and process automation
- Requirements for Data Lake provision
- Possibilities with regards Data Science and Machine Learning
- Ensuring securtiy, quality and reliability
- Building a roadmap with realistic milestones
Through our Data Strategy Consultancy, and our expertise in Data Analytics and Business Intelligence, we can guide you through the process of developing your Data Strategy and integrating data from a wide variety of platforms, including importing, exporting, migrating, cleansing and de-duplicating, master data management, data quality. We can assist you with building a secure, reliable and trustworthy central "one truth" data model, and guide you through developing powerful, rich, engaging reports and dashboards that will visually tell the stories of your data.
After engaging in an initial assessment of your Data Strategy needs we will help you to build an effective Data Strategy. With you we will map out your data journey. We will start where you want to start and will work at a pace dictated by and appropriate for you. We will advise, guide and mentor your team to ensure that you get the best Business Intelligence solution in an affordable, appropriately paced, achievable and supportable manner.
A Data Strategy should drive a data analytics roadmap consisting of many milestones along the way, rather than attempting to deliver a single long term solution.
