Rakesh Jain

Unveiling the Importance of Data Lineage in ETL Understanding the journey of your data is crucial for maintaining accuracy and trust. Let’s explore the significance of Data Lineage in the ETL (Extract, Transform, Load) process! What is Data Lineage? Data lineage tracks the flow of data from source to destination, showing how data has been transformed along the way. This transparency ensures that data integrity is maintained throughout its lifecycle. Example Scenario: - Tracing Sales Figures: Tracing a sales figure in a report back to the original transaction in the point-of-sale system. This helps in verifying the accuracy of the data and understanding its transformations. Why is Data Lineage Important? 1. Data Transparency: Provides a clear view of the data’s journey and transformations. 2. Error Tracking: Helps in identifying and correcting errors by tracing data back to its origin. 3. Regulatory Compliance: Supports compliance by maintaining detailed records of data flows and transformations. Key Benefits: - Improved Data Accuracy: Ensures that data is accurate and transformations are properly tracked. - Enhanced Trust: Builds trust in data by providing transparency into its origins and transformations. - Operational Efficiency: Facilitates troubleshooting and data quality management. Ready to enhance your ETL process with comprehensive data lineage tracking? Stay tuned for more insights and tutorials on leveraging ETL processes in your projects! 🎥🔔 Please follow Mr.Uwayo Jacques,MSc IT,MBA,B-Tech IT for more such content. #Mission100AzureDataEngineer #AzureStorage #CloudStorage #MicrosoftAzure #DataStorage #CloudComputing #StorageSolutions #CloudData #AzureBlobStorage #azure #azuredataengineer #msazure #ADE #AzureDataFactory #DataEngineering #ETL #DataLineage #BigData #DataManagement

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With the kind of voter response seen in phase 1 and 2 , it’s high time that we enforce compulsory voting & link that to acceptance of IT return , eligibility for Kisan Samman Nidhi , MNREGA , free ration, Health Insurance , driving licence,passport , bank withdrawal , UPI & every other social benefit . With so much of digitisation in place , this is easily & economically doable and is absolutely must to bring in place a 100% consciously chosen government . This will be one of the first pillars to bring about accountability in Governance and give the best possible ROI for the extremely costly election process . Further , with majority of the population across the spectrum now atuned to securely handling money through digital means , the most vital element of survival , its time we move to process of casting vote through a mobile App using multi factor authentication . We may still retain a few physical polling booths for those who still claim challenges in using an App . With secured anonimization of voter identity , this will eliminate the fear of being victimized for allegiance exposed through App based voting . Above will ensure massive reduction in cost of conducting free and fair elections , time, logistics and ensure 100% participation .

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Creating a dashboard with some random data in #streamlit, no doubt streamlit is awesome app which will help to create app in snowflake / python Snowflake Python Software Foundation #snowflake #streamlit #snowpark #dataanalysis

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The first quality for any leader is to know every member of his team have an unique style and to know the respective style.. And that gives a collaborative success. Rather asking everyone to do everything.. the best way is you make people deliver in what they are best at.

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#indianculture #indianfestival In the Bhagavata Purana, there are verses describing Krishna’s argument with the people of Vrindavan and his reasoning for honoring Govardhan Hill rather than Indra. Here are some key verses with explanations for this section: Verse 10.24.5 Translation: “My dear father, kindly listen to me. There is no need to worship Lord Indra.” Verse 10.24.6 Translation: “One should worship the earth, which produces grains, as well as the mountains and cows, which help us to sustain our lives.” Verse 10.24.8 Translation: “Being satisfied by the performance of duty, one should worship the natural environment, including Govardhan Hill.” Verse 10.24.18 Translation: “Persons who take care of cows, who carry the sticks to herd the cows, and who keep themselves in the mode of goodness by protecting animals should worship Govardhan Hill.” Verse 10.24.26 Translation: “With this ritual, Krishna convinced the cowherd men to worship Govardhan Hill and cows, rather than the demigod Indra.” Here Krishna persuades the people of Vrindavan, who were cowherds. He encourages them to recognise and honor the essential sources of their livelihood that surround them—such as the land, the cows, and Govardhan Hill. Takeaway: Krishna’s wisdom encourages us to respect and cherish the sources of life close to us. His message? Every form of work and every source of livelihood is worthy of honor and devotion. Happy Govardhan Puja!

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Regulators across various Developed Countries are launching Campaigns on Algorithm Governance amongst Online Platforms, amid the ever increasing power of algorithms to influence public opinion. This is the High Time that #Indiangovernment #GoI should also launch such campaigns to ensure proper #Governance of algorithms influencing the public opinion and choices so as to ensure a #justandfair economic Growth and Market Development in India.

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Awesome AI feature by Samsung, removing language boundaries across globe .very useful case across corporates and industries to come together work together . Love this . Will like to explore how this tech can bring revolution in Private networks industry use case

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🔥 Transforming Big Data with PySpark: Empowering ETL Developers! 🚀💼 In today's data-driven world, ETL (Extract, Transform, Load) developers play a pivotal role in ensuring that data flows smoothly through pipelines, ready for analysis and insights. And PySpark is their secret weapon! 🐍✨ 🔍 How Does PySpark Revolutionize ETL? 1️⃣ Scalability: PySpark harnesses the power of Apache Spark, enabling ETL developers to process massive datasets with ease. Whether dealing with gigabytes or petabytes, PySpark scales effortlessly to meet the demands of modern data processing. 2️⃣ Flexibility: With PySpark's Python API, ETL developers can leverage their existing Python skills to manipulate and transform data. This flexibility streamlines development and empowers teams to iterate quickly on data pipelines. 3️⃣ Performance: PySpark's in-memory processing and distributed computing capabilities deliver blazing-fast performance, crucial for time-sensitive ETL workflows. By optimizing resource utilization, PySpark ensures efficient data processing at scale. 4️⃣ Rich Ecosystem: From DataFrame operations to advanced analytics and machine learning, PySpark offers a rich ecosystem of libraries and tools to tackle diverse ETL challenges. ETL developers can seamlessly integrate with other Python libraries, expanding their toolkit for data manipulation and analysis. 5️⃣ Community Support: With a vibrant community of data engineers, scientists, and developers, PySpark fosters collaboration and knowledge sharing. ETL developers can tap into this wealth of resources to learn best practices, troubleshoot issues, and stay updated on the latest developments in big data processing. 💡 Unlocking the Potential of PySpark: Whether you're a seasoned ETL developer or just starting your journey, PySpark opens doors to new possibilities in data processing. Join the PySpark revolution and empower your ETL workflows for the future of data-driven insights! 💡🌐 #PySpark #ETL #BigData #DataEngineering #DataScience #LinkedInLearning

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Optimizing spark jobs is crucial for efficient data processing. Here are some key considerations to enhance performance: - Choose the right partitioned column for parallelism to reduce data skewness. - Opt for the appropriate join method: - Broadcast join: Broadcast smaller data frames to executors for faster execution during joins. - Use Sort merge join for equi-joins as data is sorted before merging. - Determine the optimal number of partitions to define the degree of parallelism. - Minimize the use of user-defined functions and opt for SQL aggregate functions in spark for improved efficiency. - Employ Salting to reduce data skewness before partitioning, leading to better performance. - Leverage Adaptive Query Execution (AQE) for efficient query planning based on runtime statistics. These strategies include tuning shuffle partitions, optimizing joins, and addressing skew joins. Additionally, utilize file formats like Parquet and orc, serialization like Kyro, and avoid unnecessary data caching in memory. Select only required columns and partitions, and adjust driver memory, number of executors, and memory overhead as needed for optimal results. #DataProcessing #SparkJobs #Efficiency #DataOptimization #BigData #TechTips

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I just worked through the day to move my Dads ISP from a local one to Jio Fibre. He was using a local ISP and Tata Play + the set top boxes. I planned the migration just like I would plan any other analytics project. Not hot but a cold transition to ensure that I don’t disrupt the few channels that he watches everyday apart from the news of course across various news channels. We got through the implementation nice and smooth : a few bumps but he is now using a diff remote for Jio than he did for Tata Play and he just called me and was struggling to get to a simple news channel that he usually watches. The amazing thing is that he remembers the channel number at his age and that was his indexing point to reach content. That said, a few things dawned on me immediately: 1. Design and engineering for a non native app consuming population is a very diff ball game altogether 2. The median age in India is about 28-30 yrs but the estimated population of 60+ people is > 150 million people 3. Imo, most of the designs today on app consumption and engineered access devices for the same assume a level of familiarity and knowledge to how to access and watch content, however; we need to understand that these are not applicable to everyone and esp so for older folks. 4. There is also a fear on clicking certain apps because they feel this would be a paid app and they are not sure of the same 5. Imagine a migration of your data from one device to another along with the apps—kind of easy right: it’s extremely hard to do this in the case of a Tata Sky or even a Jio. How does one migrate preferences seamlessly and with the cost factor in mind? 6. Speed stuff : I could put imp numbers on speed dial at the touch of a button on my Nokia phone in 2002 but it’s so hard to put a simple easy to access panel to recall fav channels - granted, the ones you watch pop up, upfront but it still isn’t as easy as a speed dial button. I think this goes not just for media apps and devices but for all devices in general when it comes to access for older folks. I am 5 mins away physically from my Dad but I can only imagine what it’s like for folks who are 5 to 50 hrs away or more! I think it’s a great time for companies in India to start thinking of inclusive and more sophisticated apps and capabilities for our elders. We respect our elders and do our dharma for them. Maybe it’s time that this Dharma finds itself in inclusive and simple, intuitive design for the folks we love and care about, too! #IntuitiveDesign; #SimpleisBetter; #iDontNeedARemote; Jio ; Tata Play Ltd

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Spark code to convert a timestamp given in valid format. FIrst check whether the timestamp ends with AM or PM. Filter out those records, which doesn't match this criteria. Post that, represent the given timestamp in 24 Hours & 12 Hours Format. #SCALA #BIGDATA #SPARK Karthik K. INPUT : DATETIME 25 May 2024 10:24:00 AM, 25 May 2024 10:24:00 PM, 25 May 2024 11:24:00 AM, 25 May 2024 11:24:00 PM, 25 May 2024 11:24:00, def main(args: Array[String]): Unit = { val ss = SparkSession.builder.appName("25_05").master("local[*]").getOrCreate() import ss.implicits._ val scheme = StructType(Seq(StructField("DATETIME", StringType, true))) val df = ss.read.format("csv").option("path", "C:/Users/hp/DATETIME.txt").schema(scheme).load() 👉 // KEEP ONLY THOSE RECORDS WHICH ENDS EITHER IN AM OR PM. 👉 val df_1 = df.filter(col("DATETIME").rlike("[(PM)(AM)]$")) val df_2 = df_1.select(col("DATETIME"), 👉 // CONVERT THE TIMESTAMP IN 24 HOURS FORMAT. from_unixtime(unix_timestamp(col("DATETIME"),"dd MMM yyyy hh:mm:ss a"),"dd MMM yyyy HH:mm:ss"). as("24 HOURS FORMAT")) df_2.show(truncate = false) 👉 // CONVERT THE TIMESTAMP IN 12 HOURS FORMAT. val df_3 = df_2.select(col("DATETIME"),col("24 HOURS FORMAT"), from_unixtime(unix_timestamp(col("24 HOURS FORMAT"), "dd MMM yyyy HH:mm:ss"),"dd MM yyyy hh:mm:ss a").as("12 HOURS FORMAT")) df_3.show(truncate = false) OUTPUT:

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Unleashing your inner superpower can be deeply inspired by understanding the iconography of Lord Ganesha, the remover of obstacles and the embodiment of wisdom. Each aspect of his form represents a path to unlocking personal potential: The Elephant Head symbolizes strength and the capacity to overcome challenges with intellect. Ganesha reminds us to think big, remain steady in our pursuits, and use wisdom as our primary tool. The Large Ears teach the importance of active listening, absorbing knowledge from the world around us to make informed decisions. The Small Eyes highlight focus, reminding us to concentrate on our goals and look beyond distractions. The Trunk demonstrates adaptability, showing that we must be flexible in our approach while being strong in purpose. The Broken Tusk signifies sacrifice for a greater good. It encourages us to let go of ego and past limitations to move forward with clarity. The Large Stomach represents the power to digest the good and bad in life, teaching us resilience in all circumstances. By aligning with these symbols, we channel Ganesha's divine energy within ourselves—unleashing our own inner superpower of wisdom, perseverance, and resilience.

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The 5G will pick up not out of its hype but its simplicity for high data rates, as data growth is imminent in near future, not video but prominently XR/VR. Deployment in scenarios like in India is another case to suffice the data need for heavy population, it is very much required. As opensignal draws it like .. https://lnkd.in/gcMSRAfY

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Few words that define the life of a #productmanager# Multi-tasking, Target Focused, Timely Delivery, No Distraction, Precision & sometimes “Fun at work” etc. After a lot of observations, I discovered all these around me during my daily travel to work in Bengaluru. How? – “Auto Wala’s in Bengaluru”. They exhibit all the characteristics of a Good Product Manager. Well, few pointers some of you may agree - Multi-Tasking – Can ride the auto as well as finish all-important Concalls for the day (as their headphone or earbuds are constantly on & interacting). Target Focused – No matter if it’s raining, heavy traffic, route diversion, potholes, they find they ways & means to meet the destination. Timely Delivery – Traffic could be a nightmare for others not for them. They always deliver on or before time. Precision – No matter how fast or slow they ride; they make sure at least no harm to their stuff. No Distraction – No matter if follow riders are shouting, starting or any other thing, they do not get distracted. They just continue with their own stuff. Fun at Work – Most essential element. If IPL season is on, you may find many enjoying the same along with journey. #productmanager#  #magicalbengaluru#  #citywithitsownuniqueness#

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Merger between Reliance group owned viacom18 and Disney Star is complete and the merged entity is known as Jiostar. It appears that Disney owned Star Studios and Viacom18 owned Viacom18 Studios which produces and distributes movies are not part of the merger amid the later producing only one movie and Star Studios nothing in 2024. Paramount group has exited from India selling its remaining 13.01% stake in Viacom18 to Reliance group though paramount will continue to license its streaming content along with license to operate channels such as MTV. After cash infusion of $1.4 bn by Reliance, the merged entity Jiostar is valued at $8.5 bn and will be owned by Disney 36.84%, 16.34% by RIL and 46.82% by Viacom18 which in turn is owned by RIL (70.49%), Network18 (13.54%) & Bodhi Tree Systems (15.97%). With this, Disney’s stake is valued at only $3.1 bn. Star India posted loss of Rs.12548 cr for FY24. Merger itself is due to the challenges Television channels are facing with ‘cord-cutting’ – a term used to refer subscribers cancelling cable TV and DTH to moving to streaming. https://lnkd.in/ggYsfSpf The fate of digital streaming platforms Hotstar and JioCinema is not clear. The merged entity has sports rights for cricket, football etc. IMO, the possible outcomes are: 1. A single, common subscription fee for both Hotstar and JioCinema with JioCinema hosting all sports streaming and Hotstar for all remaining entertainments. 2. JioCinema is purged and all the content including sports available in Hotstar. 3. Separate subscription fees for Hotstar and JioCinema with JioCinema streaming sports content. Another possibility is that with 100+ channels and overlapping in many markets ('Star' and 'Colors' brands) - e.g., Colors Bangla and Star Jalsha competing in same segment in same market, realignment will happen with some channels getting purged or contents swapped. With the joint venture emerging as one of the largest media entities, it may have more influence with cable distribution companies and DTH operators on carriage fees. https://lnkd.in/gnPHCAdf

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Mastering Surrogate Key Assignment in ETL To ensure consistency and efficiency in data warehousing, Surrogate Key Assignment is a crucial step. Let’s explore its role and importance! What is Surrogate Key Assignment? Surrogate key assignment involves assigning unique keys to records in dimension tables, avoiding the use of business keys from the source systems. This helps maintain consistency and avoids potential conflicts. Example Scenario: - Generating Surrogate Keys for Customer Records: Creating unique surrogate keys for customer records in the data warehouse to replace the customer IDs from the CRM system. This ensures that each record is uniquely identifiable and avoids duplication. Why is Surrogate Key Assignment Important? 1. Data Consistency: Ensures that each record has a unique identifier, preventing conflicts. 2. Integration: Simplifies the integration of data from multiple sources. 3. Performance: Improves the performance of data retrieval and reporting. Key Benefits: - Unique Identification: Each record is uniquely identifiable, ensuring data integrity. - Simplified Integration: Easier integration of data from different systems without conflicts. - Enhanced Performance: Improves the efficiency of data queries and reports. Ready to enhance your ETL process with effective surrogate key assignment? Stay tuned for more insights and tutorials on leveraging ETL processes in your projects! 🎥🔔 Please follow Mr.Uwayo Jacques,MSc IT,MBA,B-Tech IT for more such content. #Mission100AzureDataEngineer #AzureStorage #CloudStorage #MicrosoftAzure #DataStorage #CloudComputing #StorageSolutions #CloudData #AzureBlobStorage #azure #azuredataengineer #msazure #ADE #AzureDataFactory #DataEngineering #ETL #SurrogateKeyAssignment #BigData #DataIntegration

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Spark Query to create a new column based on age column in the table. #BIGDATA #SCALA #SPARK Karthik K. def main(args:Array[String]):Unit={ val ss = SparkSession.builder.appName("WHEN_OTHERWISE").master("local[*]").getOrCreate() import ss.implicits._ val data = List(("M",17),("F",25),("M",30),("F",35),("M",10)).toDF("Gender","Age") val df_with_age_remark = data.select(col("Gender"),col("Age"),when(col("Age")>=18,true).otherwise(false).as("IS ADULT")) println("Printing Age Remarks") df_with_age_remark.show() OUTPUT:

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