Modern Data Platform Architecture - Part 1
Part 1 of our data platform architecture series.
How do organizations make sense of the explosion of internally and externally generated data? Over the past 20+ years, data warehouses have been the mainstay, however, given the evolution of cloud and integration architectures (e.g. microservices) as well as the proliferation of streaming data sources and devices, a traditional modeled data warehouse is no longer sufficient.
Digital workplaces in the age of the Coronavirus
The coronavirus has essentially forced everyone, almost globally to work from home. Project-focused workforces are well versed in remote and digital collaboration but those in BAU roles are less adept in this area. With a multitude of tools and software companies will need help transitioning work practices, building online ways of working, strengthening networks and cloud applications and optimising software license spend.
2020 Wakeup Call, challenges for local government
Severe bushfires and the global impacts of the corona virus have derailed what was hoped to be a year of recovery. This has given us cause to reflect on what the biggest issues facing our generation are and roles local governments need to play in order for us to survive the major disruptive trends and environmental challenges of the next few decades.
What’s next for non-bank lending
With banks realing from a raft of post-royal comission compliance and remendation issues, non-bank lending has been booming, growing roughly 15% p.a. for the past 3 years. Non-bank issued RMBS’ has double as compared to the prior 2 year period. But what are the biggest challenges non-bank lendors face and how will they consolidate the small beach-head they have grabbed from the big banks in the residential mortgage market.
Transaction Categorisation, what about Product Categorisation?
Australian financial services has been obsessed with spend categorisation, but are they ready for the next wave of data that wil be heading their way. Product level data is the holy-grail of behavioural analytics but taiming that data set is harder than you think. This is definitely a high value banking AI use case.
Unifying data management
Walking into any organisation, the one thing we’ve found that all companies have in common is that, various aspects of the data management competency are claimed by different people with very little connectivity between them. In other words, fragmented ownership of a poorly defined area of responsibility.
Cognitivo has developed a unified approach to data management that incorporates privacy, information security, records management and data quality into a single Risk Management Framework aligned to ISO 31000 the Risk Management standard.
Innovation in local government
There’s been a flurry of investment in digital and data-driven transformation in Australian local government. This has been spurred on by Malcolm Turnbull’s 2016 Smart Cities Plan. However how much real innovation have you seen across Australian local councils? The opportunities, the technology both exist. The mindset doesn’t
You must deal with re-identification risk before sharing data but your Privacy Impact Assessments are inadequate
The digital economy is characterised by data-driven ecosystems. Organisations have recently started to experiment and engage in data commercialisation and data sharing initiatives in order innovate with data. However, few have been able to assess the the risk of re-identification and some organisations have been caught out. Do not sleep well at night, Your current PIA’s will not save you!
Data-driven, but first we must tackle the Enterprise Data Quality challenge
Competing effectively in the digital age means being data-driven to make the right long term and short term decisions. However the quality of your decisions will be proportional to the quality of your facts. Data quality is the critical stable foundation for your organisation to transition to a data-driven and AI enabled organisation.
