Q&A with Sadiqah Musa, Co-Founder at Black In Data

Sadiqah Musa, Co-Founder at Black In Data, is also an experienced Senior Data Analyst at Guardian News and Media with a demonstrated history of working in the energy and publishing sectors. She is skilled in Advanced Excel, SQL, Python, data visualization, project management, and Data Analysis and has a strong professional background with a Master of Science (MSc) from The University of Manchester.

As people become more aware and concerned about their data, the need for a regulating body will emerge, and organizations’ accountability will be mandated.



MEDIA 7: Could you please tell us a little bit about yourself? What inspired you to pursue a career in Data Analytics?
SADIQAH MUSA:
My name is Sadiqah Musa, I am a Co-Founder of Black in Data, a movement I started to push for inclusivity and diversity in the Data Analytics Industry. My current role is as a Senior Analyst at Guardian. Data Analytics found me as  I originally started my career as a geophysicist, focusing on the exploration of the oil and gas industry and analyzing seismic data. When people ask me, what inspired me to pursue a career change to Data Analytics, I always give an honest and real answer. I didn’t have a sort of epiphany moment where I realized Data Analytics was the new future and therefore I needed to be part of that game, instead, it was simple. At the time when I was considering other career options, there was a huge bust in the oil and gas industry, this is fairly standard and part of the ‘Boom Year, Bust Year’ cycle, however, I wanted a career to give me more stability. Therefore, Data Analytics was this new stable career field, which also allowed me to bring my technical skills of analyzing seismic data for 8 years and general comfort with the skillset I had already had.


M7: What impact do you think analytics & big data will have in the next 5 years?
SM:
I think two major things will happen in the next 5 years: There will be a push in Machine Learning Algorithms and discussions around the Ethics of AI. In terms of Machine Learning Algorithms, this is something that is already happening, but not on a scalable platform/level. The platforms we currently use to create machine learning algorithms are open-source and free, but you will need additional expensive software to turn all of your algorithms into a real, tangible product. At the moment, I'm noticing a shift in this situation, with the software becoming more accessible. As a result, I believe there will be a greater shift in machine learning and natural language processing in the future, where the algorithms will recognize speech and perform functions independently. Discussions on the Ethics of AI are also being held, but as the AI industry continues to grow so will our concern about its morality. A particular area is the biases within the algorithms that people have created, this is an industry that is not being regulated. When we look at things like facial recognition data, we can see that millions of images of our data are being stored without our knowledge. As people become more aware and concerned about their data, the need for a regulating body will emerge, and organizations’ accountability will be mandated.


Some companies and sponsors appear as incredibly supportive and in alignment with our organization however, they fail to provide the financial support needed as well as offer their resources to push our organization further.



M7: What have been your two biggest challenges as a co-founder at Black in Data, and how did you tackle them?
SM:
Our biggest challenge has been a reluctance to follow through with the discussions regarding implementing change and diversify the workplace. Whilst we have inspired a lot of initial interest and support regarding our movement, the difficulty lies within having our sponsors or facilitating companies commit to tangible change and action. However, we have been working to resolve this and openly having these discussions with our proposed sponsors. Also, another challenge we face, as many non-profit organizations must face, relates to our finances. Some companies and sponsors appear as incredibly supportive and in alignment with our organization however, they fail to provide the financial support needed as well as offer their resources to push our organization further.


M7: You have recently partnered with CodeUntapped, Frocentric_tech and Google Digital Garage. Could you please tell us about some of the developments that all of you at Black in Data are excited about?
SM:
At Black, In Data we are most excited about our latest partnership with CodeUntapped. It is a partnership where we get people from BID, put them into a training scheme with CodeUntapped and then put them into Jobs with amazing Organisations. The training scheme lasts for 6 weeks, is completely paid and by the end of the training scheme, the candidates are placed into the physical role that they have been training for. Once contracted for roughly 9 to 12 months, training continues. The usual outcome is securing a permanent role with the company. With Frocentric, this is an exciting person of the color networking data-industry site. It strives to connect all the different tech sectors to one platform where we can all network and support each other. It ranges from Black Founder of Data Science, AI Companies and Data companies and bringing them together to break down the compartmentalized and fractured industry. Finally, Google Digital Garage is an incredible platform that enables us to provide soft skills training ranging from CV writing to Google Digital analytics.


Traditionally people used to consume their news via structured platforms, however social media is allowing you to get the raw content from the people that are being the most impacted.



M7: What do you see as the most noticeable change right now happening in the workforce, encouraged by the rise of social media and digital technologies?
SM: 
The most noticeable change happening in the workforce is down to the impact of social media being used as a tool for awareness and awakening. Traditionally people used to consume their news via structured platforms, however social media is allowing you to get the raw content from the people that are being the most impacted. This has been fantastic for people of color, trying to educate on their lived experiences, share them and finally bringing it to the fore so that organizations have to address it. Topics typically neglected as well as deemed taboo have now been brought to light, forcing companies to evaluate their workplace treatments and biases.


M7: What is your advice to the young women who are starting out their careers in Data Analytics?
SM:
The most important thing to do is ensure that you have all of the necessary technical skills, such as being extremely proficient in Statistics, which is a critical component of Data Analytics. One thing I was never told about that I now realize is the significance of, is being able to do storytelling with Data. Usually, you might just think analyzing your data and presenting your findings is enough but you need to master how to explain your findings very well. It is also easy to second-guess yourself, so you need to be confident in your ability and trust yourself. Ultimately, I’d say be kind to yourself. Growing up, I was exceptionally scared of failure but it is all those mistakes that have shaped me into the analyst that I am today!

ABOUT BLACK IN DATA

Black in Data is a collaborative movement for people of colour, striving to promote equality of opportunity and representation within the data industry. Diversity and equality at work is crucial not only for social justice, but also for the development of a flourishing data and technology industry, able to adapt in a dynamic world. The face of the workforce is changing, and  every industry benefits from the greater breadth of knowledge, skills and personal experience that this greater diversity brings. Black in Data aims to energise and accelerate this pace of change.

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Now generally available, and ready for both analytical and transactional processing for apps originally built on MongoDB. Announced in public preview in early 2023, SingleStore Kai is an API to deliver over 100x faster analytics on MongoDB® with no query changes or data transformations required. Today, SingleStore Kai supports BSON data format natively, has improved transactional performance, increased performance for arrays and offers industry-leading compatibility with MongoDB query language. Projections: To further advance as the world’s fastest HTAP database, SingleStore has added Projections. Projections allow developers to greatly speed up range filters and group by operations by introducing secondary sort and shard keys. Query performance improvements range from 2-3x or more, depending on the size of the table. With this latest release, SingleStore becomes the industry’s first and only real-time data platform designed for all applications, analytics and AI. SingleStore supports high-throughput ingest performance, ACID transactions and low-latency analytics; and structured, semi-structured (JSON, BSON, text) and unstructured data (vector embeddings of audio, video, images, PDFs, etc.). Finally, SingleStore’s data platform is designed not just with developers in mind, but also ML engineers, data engineers and data scientists. “Our new features and capabilities advance SingleStore’s mission of offering a real-time data platform for the next wave of gen AI and data applications,” said Nadeem Asghar, SVP, Product Management + Strategy at SingleStore. “New features, including vector search, Projections, Apache Iceberg, Scheduled Notebooks, autoscaling, GPU compute services, SingleStore Kai™, and the Free Shared Tier allow startups — as well as global enterprises — to quickly build and scale enterprise-grade real-time AI applications. 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data.world | January 24, 2024

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Big Data Management

The Modern Data Company Recognized in Gartner's Magic Quadrant for Data Integration

The Modern Data Company | January 23, 2024

The Modern Data Company, recognized for its expertise in developing and managing advanced data products, is delighted to announce its distinction as an honorable mention in Gartner's 'Magic Quadrant for Data Integration Tools,' powered by our leading product, DataOS. “This accolade underscores our commitment to productizing data and revolutionizing data management technologies. Our focus extends beyond traditional data management, guiding companies on their journey to effectively utilize data, realize tangible ROI on their data investments, and harness advanced technologies such as AI, ML, and Large Language Models (LLMs). This recognition is a testament to Modern Data’s alignment with the latest industry trends and our dedication to setting new standards in data integration and utilization.” – Srujan Akula, CEO of The Modern Data Company The inclusion in the Gartner report highlights The Modern Data Company's pivotal role in shaping the future of data integration. Our innovative approach, embodied in DataOS, enables businesses to navigate the complexities of data management, transforming data into a strategic asset. By simplifying data access and integration, we empower organizations to unlock the full potential of their data, driving insights and innovation without disruption. "Modern Data's recognition as an Honorable Mention in the Gartner MQ for Data Integration is a testament to the transformative impact their solutions have on businesses like ours. DataOS has been pivotal in allowing us to integrate multiple data sources, enabling our teams to have access to the data needed to make data driven decisions." – Emma Spight, SVP Technology, MIND 24-7 The Modern Data Company simplifies how organizations manage, access, and interact with data using its DataOS (data operating system) that unifies data silos, at scale. It provides ontology support, graph modeling, and a virtual data tier (e.g. a customer 360 model). From a technical point of view, it closes the gap from conceptual to physical data model. Users can define conceptually what they want and its software traverses and integrates data. DataOS provides a structured, repeatable approach to data integration that enhances agility and ensures high-quality outputs. This shift from traditional pipeline management to data products allows for more efficient data operations, as each 'product' is designed with a specific purpose and standardized interfaces, ensuring consistency across different uses and applications. With DataOS, businesses can expect a transformative impact on their data strategies, marked by increased efficiency and a robust framework for handling complex data ecosystems, allowing for more and faster iterations of conceptual models. About The Modern Data Company The Modern Data Company, with its flagship product DataOS, revolutionizes the creation of data products. DataOS® is engineered to build and manage comprehensive data products to foster data mesh adoption, propelling organizations towards a data-driven future. DataOS directly addresses key AI/ML and LLM challenges: ensuring quality data, scaling computational resources, and integrating seamlessly into business processes. In our commitment to provide open systems, we have created an open data developer platform specification that is gaining wide industry support.

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