Foster a data driven culture
The coming economic downturn will impact businesses in four major areas: the funding environment, purchasing power of customers, macroeconomic conditions, and internal operations. Businesses that will survive and thrive through this scenario will need effective decision making based on a data driven culture.
Digital transformation is how you compete and win today. It’s the path to better serve customers, build better products, and empower employees. And data is the foundational resource in this process, allowing you to transform and uncover the insights you need to drive your business forward.
This approach is already used in the business model of tech startups, which have data engineering teams to drive efficiency and profit. Startups and Large Corporates can afford the pay and retention schemes however small business owners lack an overview of the efficiency and profit gains that will grow and sustain their companies.
Data science is an interdisciplinary field of scientific methods, processes, algorithms and systems to extract knowledge or insights from data in various forms, either structured or unstructured.
Data engineering is a subset of Data Science and requires an advanced skillset and is in high demand across the globe. The various job subsets include Data [scientists, analysts, modelling, mining etc]. ‘Big Data’ approach is also advocated using Apache, Scala, Python.
Data engineering is a cornerstone of data-drivenness. There is a great deal of value that can be derived from using data engineering to drive decision-making. Practical examples of what a data engineer does day to day and why you should care.
Financial Crime: This is an urgent and ongoing issue to tackle. This takes the time and attention of the data engineering team. A solution would be to distribute data tools within the front-line team, which saves money also.
Fintech: Focus on building a Single Source of Truth (SSOT) and apply logic to define a ‘Unified user profile’. Use this focus on catching ‘Money mules’ to counteract fraudulent activity and optimize products.
Establish trusted ‘Data sources’ and acquire velocity i.e. the optimum is to analyse data trends in real time as opposed to a batch (static) method. Take the advantage of using regular Tools before applying in-house software (tailored) tools. Data engineers will need knowledge of ‘DevOps domain’ using tools i.e. Sketcher on Cloud. And ‘Ingest data’ using tools 1.e. talend, Airlow etc.
‘Big Data’ approach done using Apache, Scala, Python. Tools referred are Kafka, SnowPlow for ‘Streaming’ and Redshift, Snowflake, SQL for ‘Warehousing’.
Know Your Customer (KYC): Provide analysis to ensure customers passed through the compliance stage can be verified.
Democratise Data Engineering
The salient (take away) point is to democratise data engineering due to the paucity of data engineers in the workplace. The approach would be “Make SQL Great Again”! Training your workforce to write simple SQL code would help drive a data-driven culture
Open Data Initiative
On April 21st Microsoft, the world’s most valuable tech firm joined a fledgling movement to liberate the world’s data. The company plans to launch 20 data-sharing groups by 2022 and give away some of its digital information, including data it has gathered on covid-19.
Learning & Development
There are widely available digital learning platforms which deliver excellent resource support and free access i.e. MOOC (Massive Open Online Courses) from Educational providers. These “Open Learning Platforms” can be used to provide career & training tracks, to support apprenticeship for companies. UKBT, Leeds University, FutureLearn and Tech Mums have developed a range of online courses to help enhance your digital skills.
LBAcademy provides a curriculum to help entrepreneurs develop their concepts in the digital hub. This provides entrepreneurs with knowledge and insight, with flexibility built in to the delivery (of the programme) to accommodate individual needs as they arise.
A data driven culture can be enabled by the CEO/Business owner and have the message trickled downwards, through actual simple steps of asking for the data behind opinions or decisions.