Happy New Year,

As we reflect on 2025 and its significance for Dataphyte Academy, we worked hand in hand with journalists, researchers, students, lecturers, academics, civil society organizations, and several international partner organizations.

Our collaborations led to the commissioning of reports, the delivery of multiple trainings, both online and in person, the participation in key events, and the expansion of our network to over 1,500 individuals across institutions and states in Nigeria, as well as selected African countries.

Our trainings have supported media participation and academic work across various countries and institutions, strengthening data interpretation for journalism, advocacy, research, and digital innovation.

Some of our key accomplishments last year include hosting eleven editions of the online Data Story Lab, visiting seven campuses to introduce data journalism and accountability practices, and organizing physical training focused on climate change, biodiversity, and other initiatives in partnership with international organizations.

We are deeply grateful to everyone who made these achievements possible.

Looking ahead to the coming year, we aim to deepen our engagement, more personally, with institutions, media organizations, research centers, and government bodies in Nigeria and across Africa.

As we move toward 2026, we look forward to building a unified community platform while developing data analytics projects and programs that will further strengthen analysis and storytelling.

Please feel free to reach us at academy@dataphyte.com and copy the coordinator at kehinde@dataphyte.com.

Warm regards,
Dataphyte Academy Team

Our Top Trainings for the Year

We are proud to highlight several impactful trainings we coordinated throughout last year, as well as the partner organizations that supported us in reaching audiences across Nigeria and other countries. The outcomes of these trainings include multiple reports, programs, and projects initiated by participants, many of which were published across various media outlets, amplifying both their work and the mission of Dataphyte Academy.

Thank you for your persistence, your trust in Dataphyte Academy, and your continued commitment to telling stories grounded in your communities.

Resources available for you:

As an offshoot of several training session, here are available materials and tools that you can engage to refresh memories;

1. Videos resources on Practical Data Journalism, Infographics Design

2. Data application of reporting Gender, Solutions Journalism, Audit Report, COP

3. Resources on how to use AI tools and Geospecial tools

4. Databases on Climate Change and Migration

All our videos are available on Dataphyte Academy Youtube Channel. We also have our Goloka and Nubia tool that helps researchers and storytellers in data gathering and data-driven reports.

Open for Partnership

In the year ahead, we aim to expand our training programs in data analytics, data journalism, research, and artificial intelligence across a wider range of institutions and organizations. These efforts are guided by our commitment to strengthening practical skills and advancing data-driven practices.

Beyond this growth, our long-term vision is to extend these training resources across multiple countries, promoting data literacy and equipping professionals, students, and institutions with the tools needed to make informed, evidence-based decisions. By scaling our programs regionally and globally, we seek to foster a more inclusive and resilient data ecosystem.

Kindly reach out to us at academy@dataphyte.com and copy the coordinator at kehinde@dataphyte.com.

We are pleased to invite you to the Dataphyte Academy Data Story Lab 11, scheduled for Saturday, 21st December 2025, from 10:00 AM to 2:00 PM (WAT). This edition of the Lab is designed to help participants strengthen their ability to turn raw datasets into clear, compelling, and impactful stories.

Data Story Lab 11 focuses on building practical skills for working with data, particularly for journalists, researchers, and communicators who want to improve how they analyse information and communicate insights to diverse audiences. The session will emphasize hands-on learning, using simple and accessible tools to move from analysis to storytelling.

Participants will be guided through practical approaches to understanding data, identifying meaningful patterns, and crafting narratives that make complex information easier to understand and more engaging.

Register now

Key focus areas include:

• Simple analytical techniques using spreadsheets

• Transforming datasets into compelling stories

• Where and how to find data on a wide range of issues

• Tools for analysing and making sense of complex datasets

The workshop will be held online via Zoom, attendance is free, and the session will be recorded. The training will be facilitated by Kehinde Ogunyale, Speaker and Coordinator at Dataphyte Academy.

We encourage you to register early and come prepared to learn, share ideas, and strengthen your data storytelling skills.

Register now: https://bit.ly/DSL-11

We look forward to having you join us for another engaging and practical Data Story Lab.

Register now

Follow us on YouTube for previous training videos: https://www.youtube.com/@DataphyteAcademy/videos

We are live for the ninth edition of the Dataphyte Academy “Data Story Lab 9.0”, focused on showing you practical ways to analyse and report compelling stories from financial data.

Register Here

During this free workshop, you will:

• Learn how to understand and interpret complex audit data.

• Discover how to turn finance data into clear, engaging narratives.

• Build your confidence in analysing and communicating financial information effectively.

Don’t miss this opportunity to level up your data reporting skills and connect with other data storytellers.

See you in the training!

Best regards,

The Dataphyte Academy Team

We are excited to invite you to the Dataphyte Academy “Data Story Lab 8.0” on Saturday, September 27th, at 10:00 AM WAT. This edition of the Lab is focused on equipping journalists with the tools and knowledge needed to effectively cover the UNFCCC Climate Change Conference. As one of the most significant global platforms for climate policy, the conference presents a unique opportunity for journalists to deepen their understanding of international negotiations, climate commitments, and the real-world implications for communities and ecosystems.

The session aims to be a practical, hands-on experience that helps participants navigate the complexities of climate diplomacy and policy reporting. Journalists will learn how to identify key story angles, interpret climate data, and engage audiences through compelling, solution-oriented narratives that connect global discussions to local realities.

Register Here

During the workshop, you will learn:

• How to interpret and report on climate negotiations and policy outcomes – including understanding key terms, decision-making processes, and the significance of various climate agreements.

• How to identify and develop impactful, solution-oriented story angles – with a focus on connecting global climate discussions to local and regional contexts.

• How to use data and expert insights to strengthen climate storytelling – ensuring accuracy, clarity, and audience engagement in reporting.

The training will run for three hours (recorded via Zoom) and is intended to foster an exchange of ideas and best practices around the use of data in storytelling. Speaking at the training are Abludkareem Mojeed and Vivan Chime, both experienced climate journalists and Kehinde Ogunyale, Coordinator of Dataphyte Academy.

Register now to secure your spot and share the stories or topics you would like us to discuss during the session. You can also suggest additional topics or resources related to climate journalism.

Register Here

Missed our Data Story Lab series? We’ve got you covered! Catch up on Sessions on our new YouTube channel: https://youtube.com/@DataphyteAcademy

We look forward to seeing you there.

Best regards,

The Dataphyte Academy Team

We are live for the fifth edition of the Dataphyte Academy “Data Story Lab 5.0” focused on enhancing the capacity of journalists to analyse and report data in the context of solution-focused journalism.

Register Here

During this free workshop, you will:

• Learn how to generate impactful solution-driven stories using data

• Analyse data to question solutions approaches and insights

• Communicate your data-driven stories effectively to your audience

You can also join the training live on YouTube:

Don’t miss out on this practical and knowledge-packed session.

See you in the training.

Best regards,

The Dataphyte Academy Team

This is to remind you that the fifth edition of the Dataphyte Academy “Data Story Lab 5.0” is happening today at 11:00 AM WAT.

This edition is focused on enhancing the capacity of journalists to analyse and report data in the context of solution-focused journalism.

Register Here

During the workshop, you will:

• Learn how to generate impactful solution-driven stories using data

• Analyse data to question solutions approaches and insights

• Communicate your data-driven stories effectively to your audience

The free training will run for three hours (recorded via Zoom), and is intended to foster an exchange of ideas and best practices around the use of data in storytelling.

Register now to secure your spot and share the stories or topics you would like us to discuss during the session. You can also suggest additional topics or resources related to data journalism.

Register Here: https://bit.ly/DataStoryLab5

Missed the previous editions of our Data Story Lab series? We've got you covered!

Watch the Sessions Here

We look forward to seeing you there.

Best regards,

The Dataphyte Academy Team

We are excited to invite you to the Dataphyte Academy “Data Story Lab 5.0” on Saturday, April 26th, at 11:00 AM WAT. This edition of the Lab is focused on enhancing the capacity of journalists to analyse and report data in the context of solution-focused journalism.

The session aims to be a practical, hands-on experience designed to help participants strengthen their storytelling by using data to highlight solutions and development-focused reporting.

During the workshop, you will:

• Learn how to generate impactful solution-driven stories using data

• Analyse data to question solutions approaches and insights

• Communicate your data-driven stories effectively to your audience

The training will run for three hours (recorded via Zoom), and is intended to foster an exchange of ideas and best practices around the use of data in storytelling.

Register Here

Speaking at the training are Chibuike Alagboso, the Director of Media Programmes at Nigeria Health Watch; Innocent Eteng, the Managing Director/Business Development Lead of Prime Progress and Kehinde Ogunyale of Dataphyte Academy.

Register now to secure your spot and share the stories or topics you would like us to discuss during the session. You can also suggest additional topics or resources related to data journalism.

Register Here: https://bit.ly/DataStoryLab5

Missed the previous editions of our Data Story Lab series? We've got you covered!

Watch the Sessions Here

We look forward to seeing you there.

Best regards,

The Dataphyte Academy Team

We are excited to invite you to the Dataphyte Academy “Data Story Lab 3.0” at 11 AM WAT today, February 22nd.

Whether you are a journalist, researcher, student, or simply passionate about data-driven storytelling, this session will provide you with the tools and techniques to visualise geographic data, amplify your stories, and uncover hidden insights.

Register here: https://bit.ly/DataStoryLab-3

Date: Today, February 22nd, 2025

Time: 11:00 AM WAT

This free online workshop is an opportunity to learn how to leverage GIS and mapping tools in journalism, enhancing your reports with geographic data.

During the workshop, you will:

• Learn how to enhance your reports using geographic data

• Explore practical strategies for visualising geographic data

• Analyse key reports and learn how to present data using GIS and mapping tools

• Exchange ideas with experienced journalists and experts

Register now to participate in the session.

Register Here

We look forward to seeing you there.

Best regards,

The Dataphyte Academy Team

We are excited to invite you to the Dataphyte Academy “Data Story Lab 3.0” tomorrow, February 22nd, at 11 AM WAT.

This free 3-hour online workshop is an opportunity to learn how to leverage GIS and mapping tools in journalism, enhancing your reports with geographic data.

Whether you are a journalist, researcher, student, or simply passionate about data-driven storytelling, this session will provide you with the tools and techniques to visualise geographic data, amplify your stories, and uncover hidden insights.

During the workshop, you will:

• Learn how to enhance your reports using geographic data

• Explore practical strategies for visualising geographic data

• Analyse key reports and learn how to present data using GIS and mapping tools

• Exchange ideas with experienced journalists and experts

This is more than just a workshop - it's a chance to gain practical skills and inspiration for your data storytelling journey.

Register now to secure your spot.

Register Here

We look forward to seeing you there.

Best regards,

The Dataphyte Academy Team

We are excited to invite you to the Dataphyte Academy “Data Story Lab” on Saturday, December 21st, at 2:00 PM WAT. This free 3-hour workshop is an opportunity to learn the essential processes of generating, analysing, and reporting data-driven stories.

Whether you are a journalist, researcher, student, or simply passionate about data, this session will provide you with the tools and techniques to turn raw data into powerful narratives. During the workshop, you will:

• Learn how to generate impactful data-driven stories

• Analyse data to uncover hidden insights

• Create engaging and insightful visualisations

• Communicate your data-driven stories effectively to your audience

This is more than just a workshop - it’s a chance to exchange ideas with experienced journalists and experts who will share valuable insights for data-driven reporting in 2025.

Don’t miss this opportunity to gain practical skills and inspiration for your data storytelling journey.

Register Here

Register now to secure your spot and share the stories or topics you would like us to discuss during the session. You can also suggest additional topics or resources related to data journalism.

We look forward to seeing you there.

Best regards,

The Dataphyte Academy Team

In the realm of data analysis, understanding some key concepts is essential. Data analysis is the process of inspecting, cleansing, transforming, and modeling data to discover useful information and support decision-making. In the broadest sense, data can be classified into various types like nominal, ordinal, interval and ratio, each with a specific role and analysis technique. Higher-dimensional data types like time-series, panel data, and multi-dimensional arrays are also critical. On the other hand, data quality and data management are key concepts to ensure clean and reliable datasets. With an understanding of these fundamental concepts, a data analyst can transform raw data into meaningful insights.

Data Collection

In the realm of data analysis, the concept of collection holds immense importance. As the term suggests, collection refers to the process of gathering and measuring information on targeted variables in an established systematic fashion that enables a data analyst to answer relevant questions and evaluate outcomes. This step is foundational to any data analysis scheme, as it is the first line of interaction with the raw data that later transforms into viable insights. The effectiveness of data analysis is heavily reliant on the quality and quantity of data collected. Different methodologies and tools are employed for data collection depending on the nature of the data needed, such as surveys, observations, experiments, or scraping online data stores. This process should be carried out with clear objectives and careful consideration to ensure accuracy and relevance in the later stages of analysis and decision-making.

Cleanup

The Cleanup of Data is a critical component of a Data Analyst’s role. It involves the process of inspecting, cleaning, transforming, and modeling data to discover useful information, inform conclusions, and support decision making. This process is crucial for Data Analysts to generate accurate and significant insights from data, ultimately resulting in better and more informed business decisions. A solid understanding of data cleanup procedures and techniques is a fundamental skill for any Data Analyst. Hence, it is necessary to hold a high emphasis on maintaining data quality by managing data integrity, accuracy, and consistency during the data cleanup process.

Visualization

The visualization of data is an essential skill in the toolkit of every data analyst. This practice is about transforming complex raw data into a graphical format that allows for an easier understanding of large data sets, trends, outliers, and important patterns. Whether pie charts, line graphs, bar graphs, or heat maps, data visualization techniques not only streamline data analysis, but also facilitate a more effective communication of the findings to others. This key concept underscores the importance of presenting data in a digestible and visually appealing manner to drive data-informed decision making in an organization.

Exploration

In the realm of data analytics, exploration of data is a key concept that data analysts leverage to understand and interpret data effectively. Typically, this exploration process involves discerning patterns, identifying anomalies, examining underlying structures, and testing hypothesis, which often gets accomplished via descriptive statistics, visual methods, or sophisticated algorithms. It’s a fundamental stepping-stone for any data analyst, ultimately guiding them in shaping the direction of further analysis or modeling. This concept serves as a foundation for dealing with complexities and uncertainties in data, hence improving decision-making in various fields ranging from business and finance to healthcare and social sciences.

Statistical Analysis

Statistical analysis plays a critical role in the daily functions of a data analyst. It encompasses collecting, examining, interpreting, and present data, enabling data analysts to uncover patterns, trends and relationships, deduce insights and support decision-making in various fields. By applying statistical concepts, data analysts can transform complex data sets into understandable information that organizations can leverage for actionable insights. This cornerstone of data analysis enables analysts to deliver predictive models, trend analysis, and valuable business insights, making it indispensable in the world of data analytics. It is vital for data analysts to grasp such statistical methodologies to effectively decipher large data volumes they handle.

Machine Learning

Machine learning, a subset of artificial intelligence, is an indispensable tool in the hands of a data analyst. It provides the ability to automatically learn, improve from experience and make decisions without being explicitly programmed. In the context of a data analyst, machine learning contributes significantly in uncovering hidden insights, recognising patterns or making predictions based on large amounts of data. Through the use of varying algorithms and models, data analysts are able to leverage machine learning to convert raw data into meaningful information, making it a critical concept in data analysis.

Happy new month from Dataphyte Academy!!!

You made it, yes you! An exclusive offer just for you, don’t miss the chance to master the art and science of analytics and data management. Enroll today in our November cohort for just N120,000 only (instalment plan available) and gain the knowledge to harness the full potential of data in your professional journey.

Want to become an expert data analyst or just want to learn more, fill the enquiry form.

Join our Dataphyte Academy community and follow us on our socials for more information and expert reads.

Twitter and Linkedln @DataphytAcademy.

This experience motivated me to explore the various niches within data analytics, which led to writing this article.

CHOOSING THE RIGHT SPECIALISATION FOR YOU

Before explaining why it’s essential to select a niche and highlighting common specialisations, let me share how I chose mine: risk analysis and business analytics. I evaluated my passion and experience—while I had a background in business development, my passion lay in Risk. Researching how my skills could be applied in these areas helped me decide on these niches. You can choose more than one niche if you're a driven and a curious individual like me.

To find your niche, explore the examples provided below or conduct online research—it's free and worthwhile.

COMMON DATA ANALYSTS’ SPECIALISATION

Data analytics focuses on visualising and interpreting data sets to answer specific questions. Many analysts specialise in particular fields, which allows them to fulfil unique roles within organisations. Analytics can be highly rewarding for those passionate about data, with specialisations adding value by addressing industry-specific needs. Here are some common types of data analysis:

1. Descriptive Analytics: Reviews past events to identify trends.

2. Diagnostic Analytics: Examines why something happened by comparing data sets.

3. Predictive Analytics: Predicts future outcomes based on trends.

4. Prescriptive Analytics: Identifies actions to take by using algorithms and advanced technologies like machine learning.

Now, let’s explore the most common data analytics specialisations:

1. Medical and health care analyst: The modern healthcare system produces an unimaginable wealth of data, including everything from transaction information to metrics tracked by wearable devices.

   This information could have huge implications for patient outcomes and satisfaction. Furthermore, data-driven strategies promise to help reduce the cost of care. First, however, this ever-increasing scope of healthcare data must be collected, organised, and studied. An analyst must complete these tasks in accordance with ethical standards and current legislation, including, most notably, the Health Insurance Portability and Accountability Act (HIPAA).

2. Market research analyst: Today’s digital landscape provides many opportunities to improve consumer awareness and engagement. Marketing analytics can blend creative aspirations with technical tools. This can lead to impactful outreach, getting consumers more invested in brands or ideas. Success can lead to dramatic improvements in campaign return on investment (ROI), along with greater innovation. Key tasks completed by marketing analysts involve competitor analysis and customer segmentation. These professionals work closely with marketing teams to determine which strategies are backed by data.

3.  Business analyst: A business analyst helps organisations improve processes, services, and products by analysing business needs and providing data-driven solutions. They act as a bridge between stakeholders and technical teams, ensuring requirements are met.

4. Operations research analyst: This role involves using advanced mathematical and analytical methods to solve complex organisational problems, optimise processes, and improve decision-making in areas like logistics, production, and resource management.

5. Intelligence analyst: Intelligence analysts collect, evaluate, and interpret data related to security threats. They provide actionable insights to support decision-making in law enforcement, military, or corporate sectors.

6. Risk analyst: Risk analysts help organisations identify, assess, and prioritise potential risks that could impact their business operations. They use a variety of tools and techniques to evaluate the likelihood and potential impact of different risks and then develop strategies to mitigate or manage those risks. As far as careers in analytics go, this is up there among the most interesting. 

7. Cybersecurity Analytics: Cybersecurity analytics utilises data proactively to combat today’s most devastating cyberattacks. It delves into the details of traffic analysis, network and system logs, and other resources to identify threats in real-time. The resulting analysis may reveal vulnerabilities or the earliest signs of compromise. All networks produce extensive data, but with cybersecurity analytics, this information can play heavily into threat detection, incident identification, risk mitigation, and more.

8.  Environmental Analytics: From weather patterns to watershed databases, the natural world produces a wealth of data just waiting to be collected and analysed. The growing field of environmental analytics strives to utilise this abundant data better while supporting ecological initiatives. Drawing on a blend of geographical and ecological knowledge, plus advanced skills in statistical analysis, environmental analysts are passionate about their work and determined to make a difference.

9.  Financial Analytics: Dedicated to helping organisations manage their resources, financial analysts collect and organise large volumes of external and internal financial data. This information may produce significant takeaways regarding cash flow, sales forecasting, or even shareholder value. The goal is to drive businesses towards factual, data-driven decision-making rather than relying on intuition.

10. Sports Analytics: Sports analytics brings data-driven insights to a variety of athletic events and activities. This can play into coaching strategies, injury prevention efforts, fan engagement, and more. As passion-driven professionals, sports analysts understand the power of data to impact every facet of the sports industry.

    

    WHY ALL DATA ANALYSTS SHOULD PICK A NICHE

    In such a competitive landscape, it is crucial to adopt a niche specialisation even as a freelancer or you are looking to get employed. Here are several advantages of narrowing your focus:

    1. Enhanced expertise: By specialising in a specific niche, you can deepen your knowledge and skills in a particular area of data analysis. This allows you to become a subject matter expert, which is highly valued in the industry.

    2. Reduced competition: Niche specialisation helps you differentiate yourself from the general pool of data analysts, thereby reducing the number of direct competitors. With fewer individuals possessing expertise in your chosen niche, your chances of standing out and securing job opportunities increases.

    3. Increased demand: Specialising in a niche can align your skills with the growing demands of specific industries or sectors. This positions you as a valuable asset, as companies seek professionals who possess in-depth knowledge and experience in their particular field.

    4. Higher earning potential: As a niche specialist, your unique skill set and expertise can command higher compensation. Companies are often willing to pay a premium for professionals who possess specialised knowledge and can provide valuable insights in a specific area of data analysis.

    5. Improved career progression: By focusing on a niche, you can develop a clear career path and set yourself apart from generalists. This allows for targeted skill development and increased opportunities for advancement within your chosen niche.

    SPECIALISING IN DATA ANALYTICS AT DATAPHYTE ACADEMY

    As you look ahead to exciting opportunities in data analytics and excelling, focus on building your technical expertise alongside soft skills like communication and collaboration. Dataphyte Academy offers an extensive Data Analytics and Management program, helping you gain the essential knowledge to succeed. You’ll explore database administration, programming, and niche specialisations under expert mentorship. Our next cohort begins on the 2nd of November, 2024 —take the next step by filling out our enquiry form and expect an email from us soon!

    Also click the link to join our dataphyte academy community for more real time information

    Follow us on our socials for more information and expert reads.

    Twitter and Linkedln @DataphytAcademy

    Happy Friday from Dataphyte Academy!

Why Automate SQL Backups?

Data is the backbone of any business, and without regular backups, companies are at risk of data loss due to system failure, human error, or cyberattacks. Manual backups are time-consuming and prone to oversight. Automating this process ensures:

• Consistency: Regular backups happen without manual intervention.

• Efficiency: Frees up time for database administrators.

• Reliability: Reduces the risk of human error.

By using SQL Server Agent, you can automate and schedule backups to ensure your data is secure, and your operations remain uninterrupted.

Types of SQL Backup Automations

Before diving into the process, it’s important to understand the three primary types of SQL backups that can be automated:

1. Full Backup

This is a complete copy of the entire database, including all data files. It's the foundation for other backup types. Typically, it can be scheduled yearly, quarterly, monthly, or weekly, as it requires significant storage and time to complete.

2. Differential Backup

Captures changes made since the last full backup. It is smaller and quicker to execute compared to full backups. Ideal for daily backups, providing more frequent data protection while saving space.

3. Transaction Log Backup

Backs up only the transaction log, capturing all the transactions since the last log backup. It is crucial for point-in-time recovery. Best for mission-critical databases where real-time data protection is necessary, typically scheduled every 15-30 minutes.

 How to Automate SQL Backups Using SQL Data Agent

Step 1: Open SQL Server Management Studio (SSMS)

Launch SSMS and connect to your SQL Server instance.

Step 2: Locate SQL Server Agent

In SSMS, expand your server tree and find the SQL Server Agent. This agent is responsible for automating jobs like backups.

Step 3: Create a New Job for Full Backup

1. Right-click on Jobs under SQL Server Agent and select New Job.

2. In the General tab, name your job (e.g., “Weekly Full Backup”).

Step 4: Set up Full Backup

1. Go to the Steps tab and click New to create a backup step.

2. In the Step Name, type "Full Backup Step".

3. Set Type to Transact-SQL script (T-SQL).

4. Write T-SQL scripts to perform backups. Here are examples of common backup types:Full Backup:sql

Here are sample scripts of the common backup types:

Full Backup:sql

BACKUP DATABASE [YourDatabaseName] TO DISK = 'C:\Backup\YourDatabaseName_FULL.bak'

Differential Backup:sql

BACKUP DATABASE [YourDatabaseName] TO DISK = 'C:\Backup\YourDatabaseName_DIFF.bak' WITH DIFFERENTIAL

Transaction Log Backup:sql

BACKUP LOG [YourDatabaseName] TO DISK = 'C:\Backup\YourDatabaseName_LOG.trn'

Schedule these scripts using SQL Server Agent to automate the backups.

Step 5: Create Differential and Transaction Log Backups

Repeat Steps 3-4 to create new jobs for differential and transaction log backups:

Step 6: Schedule the Jobs

1. Go to the Schedules tab in each job.

2. Click New, then configure the schedule based on the type of backup:

   • Full Backup: Schedule weekly (e.g., every Sunday at midnight).

   • Differential Backup: Schedule daily (e.g., every day at 1 AM).

   • Transaction Log Backup: Schedule frequently (e.g., every 30 minutes).

Step 7: Monitor and Manage Jobs

Once the jobs are set up, it’s important to monitor their performance:

• Job History: Right-click on the job and select View History to ensure jobs are running smoothly.

• Alerts: Set up SQL Server Alerts to notify you of any backup failures via email.

 Additional Best Practices for Automated SQL Backups

1. Store Backups Securely: Always store backups on separate drives or cloud storage to prevent data loss in case of disk failure.

2. Test Restores: Regularly test your backups by performing restore operations to ensure data can be recovered.

3. Backup Retention Policy: Define a retention policy to automatically delete old backups and save storage space.

4. Encrypt Backups: For sensitive data, consider encrypting your backups to protect them from unauthorized access.

Conclusion

Automating SQL backups using SQL Data Agent ensures that your data remains secure, reducing the risk of human error and ensuring timely backups. By leveraging full, differential, and transaction log backups, you can create a robust data protection strategy tailored to your organization's needs. With the detailed setup instructions and schedules provided, you can implement a seamless backup process in no time.

Want to become an expert data analyst or just want to learn more, fill the enquiry form or click the link to join our Dataphyte academy community.

Follow us on our socials for more information and expert reads. Twitter and Linkedln @DataphytAcademy

Happy Friday from Dataphyte Academy

Five years into my role as Head of Business Intelligence and Databases at a development finance institution, I was feeling pretty confident. We had just wrapped up an audit review with the Infrastructure Lead, CIO, and IT Risk Manager. Our disaster recovery plans were thorough. We had active replication between our headquarters and co-location site, tape backups stored securely offsite, and on-premise disk backups. We diligently monitored our disaster recovery (DR) architecture and ran routine business continuity planning (BCP) tests. After several successful rounds, we became complacent and, perhaps unwisely, eased up on the monitoring.

One day, the CIO approached me with a request to automate our database backups to the cloud. It sounded interesting but felt excessive given our existing setup. I brushed it off, confident in our current measures and automated processes. How could we possibly need more redundancy?

Fast forward a few months, and our confidence was shattered. We were struck by a ransomware attack. Our treasury, credit, and accounting applications, along with our databases, were compromised. The attackers wiped out our servers, destroyed our tape backup controller, and even breached our DR site.

Desperate to meet our Recovery Time Objective (RTO) and Recovery Point Objective (RPO), we turned to our cloud backups, which we believed were up-to-date. But when the CIO asked for the backups, I had to admit the painful truth: the last time I had manually backed up the databases was months before the attack.

Here’s where SQL Server Agent could have been a game-changer. SQL Server Agent, a tool from Microsoft designed to automate and schedule jobs, could have been used to set up automated backups, ensuring they were consistently and reliably created without manual intervention. With it, we could have minimised downtime and potentially recovered in under six hours instead of enduring a gruelling five-day recovery process.

The lesson was harsh but invaluable. SQL Server Agent isn’t just another tool; it’s a critical component of effective database management. It’s like having a personal assistant dedicated to ensuring your backups are always current.

Next week, I’ll dive into how you can harness the power of SQL Server Agent to automate your backups, saving you from the stress and disaster I faced. Stay tuned—your future self will thank you.

• Adam Bifola Raji

Virtual Data Analytics and Management Bootcamp

If you’re fascinated by the transformative power of database management and analytics, our upcoming Data Management and Analytics cohort is your gateway to mastering these essential skills. Launching in October, this course offers a comprehensive dive into the fundamentals of data management—how to effectively collect, store, and organize data.

You’ll gain hands-on experience with tools and techniques to analyze data, uncover valuable insights, and create impactful reports. We’ll explore crucial topics such as data quality, data governance, and storytelling, equipping you with the expertise to excel in any professional environment.

Seize this opportunity to refine your skills and elevate your career. Enroll in our October cohort to unlock the full potential of data and transform how you leverage data for decision-making in your professional journey.

Want to become an expert data analyst or just want to learn more, fill the enquiry form or click the link to join our dataphyte academy community.

Follow us on our socials for more information and expert reads.

Twitter and Linkedln @DataphytAcademy

Happy Friday from Dataphyte Academy

Data journalism combines traditional investigative techniques with data analysis to provide a deeper, more nuanced understanding of events. It allows journalists to go beyond surface-level reporting, offering insights that are grounded in empirical evidence. This approach has become increasingly vital in an era where misinformation and biassed reporting can easily distort the public's perception of critical issues.

In Nigeria’s 2023 elections, Dataphyte brought to bear the descriptive and prescriptive power of data journalism with the release of the Dataphyte Handbook of Data-Driven Election Reporting. It deployed data analysis to build a model that singularly predicted correctly and in detail the outcome of the 2023 presidential elections results with 98% accuracy. Premium Times, noting all pollsters who got the 2023 Presidential election results prediction wrong or who were not definitive, singled out Dataphyte as the exception: 

“Finally, Dataphyte Research conducted a “state by state ground-truthing stats,” which involved “analysing past voting patterns, voter turnouts, voter choice homogeneity, the religious homogeneity index, and so on” and “found the current scenario to be similar to that in the 2015 elections.” The media firm projected that Mr “Tinubu would win the popular votes and would be the only candidate to satisfy the spread criteria of a minimum of 25 per cent votes in two-thirds of the 36 states and FCT. The organisation said there would be no need for a run-off election. "That poll got it right,”" the paper reported.

Dataphyte’s data journalism endeavours in the election period also included creating a dashboard for live reporting and monitoring of election results on election day.

During the 2020 EndSARS protests, data journalism was vital in capturing the movement's scale and impact, countering false narratives, and ensuring marginalised voices were heard. It provided accurate data on turnout, violence, and social media, offering a comprehensive view of the events.

The power of data journalism lies in its ability to transform raw data into stories that inform, engage, and inspire action. In the context of the recent protests in Nigeria, it has proven to be an indispensable tool for journalists seeking to uphold the principles of accuracy, transparency, and accountability. As the demand for high-quality, evidence-based reporting continues to grow, so too does the need for skilled data journalists who can navigate the complexities of data and translate them into meaningful narratives.

Data Journalism a Certified Course with Dataphyte Academy

For aspiring journalists or those looking to enhance their skills, mastering data journalism is no longer optional—it's essential. Dataphyte Academy offers a comprehensive data journalism course designed to equip you with the tools and techniques needed to excel in this dynamic field. By enrolling, you will gain the expertise to harness the power of data journalism, enabling you to amplify voices, uncover truths, and make a lasting impact in the world of journalism and mass communication.

To learn more, send an email to our team today at . 

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Understanding these challenges is essential for navigating the complexities of the role and excelling in the competitive job market. Here are just a few:

1. Domain Knowledge and Sector-Specific Expertise

An often-overlooked challenge is the necessity for data analysts to understand the field from which their data is derived. This domain knowledge is crucial for interpreting data effectively and providing relevant insights. For instance, analysing healthcare data requires understanding medical terminologies and regulations, while financial data analysis demands familiarity with economic indicators, financial statements and market trends. This challenge is particularly significant for freelance data analysts who must be knowledgeable across various sectors to cater to diverse client needs. Building expertise in multiple domains enhances their ability to interpret data accurately and offer valuable insights across different industries.

2. Effective Communication and Collaboration

Data analysts must skillfully translate complex data into actionable insights for non-technical stakeholders, requiring strong storytelling and visualization. New analysts may struggle with this, while experienced ones face the challenge of aligning their findings with broader business goals and collaborating across departments.

3. Keeping Up with Technological Advancements 

The fast-paced evolution of tools and technologies in data analytics poses a challenge. New analysts may find it difficult to master numerous tools, while experienced analysts must continuously update their skills to stay relevant, balancing learning with their existing workload.

4. Data Quality and Integrity

Ensuring data accuracy, completeness, and reliability is a key challenge. Both new and seasoned analysts must meticulously clean and validate data to avoid incorrect insights and flawed decisions, requiring significant attention to detail and robust methodologies.

5. Data Privacy and Security  

Navigating data privacy concerns and regulations like GDPR and the NDPR is crucial. Analysts must protect sensitive data and ensure legal compliance, which can restrict data access and complicate handling processes. Staying informed about regulatory changes and best practices is essential for both new and experienced analysts. 

6. Managing High Expectations and Multiple Priorities  

Handling multiple projects and tight deadlines is a common challenge. New analysts may struggle with balancing these demands, while experienced analysts must manage increasing pressure while maintaining work quality and delivering actionable insights promptly.

How Dataphyte Academy Can Help

Understanding these challenges is key to navigating the chess game of data analysis. Here’s a strategic move to overcome them: Dataphyte Academy offers a meticulously crafted, structured learning environment designed to give you a competitive edge and help you tackle these obstacles effectively. 

Visit our website

It offers personalised learning pathways to help students identify and develop their niche, aligning with their strengths and career aspirations. The emphasis on hands-on projects and internships bridges the gap between theory and practice, providing real-world experience and a strong portfolio. An up-to-date curriculum and mentorship from industry experts ensure students master essential tools and stay current with technological advancements. This comprehensive approach equips aspiring data analysts with the skills and support needed to thrive in today's competitive job market.

To learn more, send an email to our team today at academy@dataphyte.com 

You can also follow us on our socials for more information and expert reads.

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Twitter: @DataphytAcademy 

Linkedin: @Dataphyte Academy

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Why Proper Data Collection Matters

Properly collected data provides valuable insights into customer behaviour, market trends, and operational efficiency. Effective data collection addresses the WHY, HOW, WHERE, and WHEN of data gathering. Without accurate data, businesses risk making decisions based on assumptions, leading to potential financial losses and missed opportunities. There are many advantages to this but we have listed a few here:

Enhance Customer Experience: By understanding customer preferences and behaviours, companies can tailor their products and services to meet customer needs more effectively, fostering loyalty and satisfaction.

Research and Development(R&D): Accurate data collection ensures the progress of R&D, thereby fostering the culture of creativity and innovation in the organisation for the acceleration of products and services.

Data Security and Compliance: Proper data collection ensures that the organisation's data is compliant with regulations like GDPR (General Data Protection Regulation) and NDPR (Nigeria Data Protection Regulation). It helps ensure proper governance and risk management of data at rest and in-use. 

Data Explosion: The daily amount of data generated is increasing exponentially due to the growth of the Internet of Things (IoT), social media, and digital transactions. Proper data collection ensures that this huge amount of data is streamed and warehoused for optimal utilisation.

Challenges in Data Collection

Proper data collection is essential but challenging. Manual entry is time-consuming and error-prone, and integrating data from various sources can lead to inconsistencies. Maintaining data quality and accuracy is an ongoing struggle, and delays between collection and company access can compromise data integrity. Additionally, the costs of collecting data from different locations pose significant challenges.

Introducing GOLOKA by Dataphyte— Goloka is a data access platform that leverages artificial intelligence to streamline and optimise Africa's data collection, warehousing, and analysis process. Fostering a dynamic collect-to-earn network empowering a vast community of data collaborators and organisations to engage in real-time, on-demand data collection and insight generation. 

This platform addresses critical challenges such as access, quality, and real-time data collection, catalyses socio-economic empowerment, and ensures data security.

Visit our website or contact our sales team today; info@dataphyte.com

Want to become an expert data analyst today, send an email to our team today at mailto:academy@dataphyte.com or or click the link to join our dataphyte academy community